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## Допълнителни книги
Книгите тук ще ви позволят да се гмурнете в теми, които са интересни за вас.
- [The Unix Programming Environment](https://www.amazon.com/dp/013937681X)
- An oldie but a goodie
- [The Linux Command Line: A Complete Introduction](https://www.amazon.com/dp/1593273894/)
- A modern option
- [TCP/IP Illustrated Series](https://en.wikipedia.org/wiki/TCP/IP_Illustrated)
- [Head First Design Patterns](https://www.amazon.com/gp/product/0596007124/)
- A gentle introduction to design patterns
- [Design Patterns: Elements of Reusable Object-Oriente​d Software](https://www.amazon.com/Design-Patterns-Elements-Reusable-Object-Oriented/dp/0201633612)
- AKA the "Gang Of Four" book, or GOF
- The canonical design patterns book
- [Algorithm Design Manual](http://www.amazon.com/Algorithm-Design-Manual-Steven-Skiena/dp/1849967202) (Skiena)
- As a review and problem recognition
- The algorithm catalog portion is well beyond the scope of difficulty you'll get in an interview
- This book has 2 parts:
- Class textbook on data structures and algorithms
- Pros:
- Is a good review as any algorithms textbook would be
- Nice stories from his experiences solving problems in industry and academia
- Code examples in C
- Cons:
- Can be as dense or impenetrable as CLRS, and in some cases, CLRS may be a better alternative for some subjects
- Chapters 7, 8, 9 can be painful to try to follow, as some items are not explained well or require more brain than I have
- Don't get me wrong: I like Skiena, his teaching style, and mannerisms, but I may not be Stony Brook material
- Algorithm catalog:
- This is the real reason you buy this book.
- This book is better as an algorithm reference, and not something you read cover to cover.
- Can rent it on Kindle
- Answers:
- [Solutions](<http://www.algorithm.cs.sunysb.edu/algowiki/index.php/The_Algorithms_Design_Manual_(Second_Edition)>)
- [Solutions](http://blog.panictank.net/category/algorithmndesignmanualsolutions/page/2/)
- [Errata](http://www3.cs.stonybrook.edu/~skiena/algorist/book/errata)
- [Write Great Code: Volume 1: Understanding the Machine](https://www.amazon.com/Write-Great-Code-Understanding-Machine/dp/1593270038)
- The book was published in 2004, and is somewhat outdated, but it's a terrific resource for understanding a computer in brief
- The author invented [HLA](https://en.wikipedia.org/wiki/High_Level_Assembly), so take mentions and examples in HLA with a grain of salt. Not widely used, but decent examples of what assembly looks like
- These chapters are worth the read to give you a nice foundation:
- Chapter 2 - Numeric Representation
- Chapter 3 - Binary Arithmetic and Bit Operations
- Chapter 4 - Floating-Point Representation
- Chapter 5 - Character Representation
- Chapter 6 - Memory Organization and Access
- Chapter 7 - Composite Data Types and Memory Objects
- Chapter 9 - CPU Architecture
- Chapter 10 - Instruction Set Architecture
- Chapter 11 - Memory Architecture and Organization
- [Introduction to Algorithms](https://www.amazon.com/Introduction-Algorithms-3rd-MIT-Press/dp/0262033844)
- **Important:** Reading this book will only have limited value. This book is a great review of algorithms and data structures, but won't teach you how to write good code. You have to be able to code a decent solution efficiently
- AKA CLR, sometimes CLRS, because Stein was late to the game
- [Computer Architecture, Sixth Edition: A Quantitative Approach](https://www.amazon.com/dp/0128119055)
- For a richer, more up-to-date (2017), but longer treatment
## System Design, Scalability, Data Handling
**You can expect system design questions if you have 4+ years of experience.**
- Scalability and System Design are very large topics with many topics and resources, since
there is a lot to consider when designing a software/hardware system that can scale.
Expect to spend quite a bit of time on this
- Considerations:
- Scalability
- Distill large data sets to single values
- Transform one data set to another
- Handling obscenely large amounts of data
- System design
- features sets
- interfaces
- class hierarchies
- designing a system under certain constraints
- simplicity and robustness
- tradeoffs
- performance analysis and optimization
- [ ] **START HERE**: [The System Design Primer](https://github.com/donnemartin/system-design-primer)
- [ ] [System Design from HiredInTech](http://www.hiredintech.com/system-design/)
- [ ] [How Do I Prepare To Answer Design Questions In A Technical Interview?](https://www.quora.com/How-do-I-prepare-to-answer-design-questions-in-a-technical-interview?redirected_qid=1500023)
- [ ] [8 Things You Need to Know Before a System Design Interview](http://blog.gainlo.co/index.php/2015/10/22/8-things-you-need-to-know-before-system-design-interviews/)
- [ ] [Database Normalization - 1NF, 2NF, 3NF and 4NF (video)](https://www.youtube.com/watch?v=UrYLYV7WSHM)
- [ ] [System Design Interview](https://github.com/checkcheckzz/system-design-interview) - There are a lot of resources in this one. Look through the articles and examples. I put some of them below
- [ ] [How to ace a systems design interview](http://www.palantir.com/2011/10/how-to-rock-a-systems-design-interview/)
- [ ] [Numbers Everyone Should Know](http://everythingisdata.wordpress.com/2009/10/17/numbers-everyone-should-know/)
- [ ] [How long does it take to make a context switch?](http://blog.tsunanet.net/2010/11/how-long-does-it-take-to-make-context.html)
- [ ] [Transactions Across Datacenters (video)](https://www.youtube.com/watch?v=srOgpXECblk)
- [ ] [A plain English introduction to CAP Theorem](http://ksat.me/a-plain-english-introduction-to-cap-theorem)
- [ ] [MIT 6.824: Distributed Systems, Spring 2020 (20 videos)](https://www.youtube.com/watch?v=cQP8WApzIQQ&list=PLrw6a1wE39_tb2fErI4-WkMbsvGQk9_UB)
- [ ] Consensus Algorithms:
- [ ] Paxos - [Paxos Agreement - Computerphile (video)](https://www.youtube.com/watch?v=s8JqcZtvnsM)
- [ ] Raft - [An Introduction to the Raft Distributed Consensus Algorithm (video)](https://www.youtube.com/watch?v=P9Ydif5_qvE)
- [ ] [Easy-to-read paper](https://raft.github.io/)
- [ ] [Infographic](http://thesecretlivesofdata.com/raft/)
- [ ] [Consistent Hashing](http://www.tom-e-white.com/2007/11/consistent-hashing.html)
- [ ] [NoSQL Patterns](http://horicky.blogspot.com/2009/11/nosql-patterns.html)
- [ ] Scalability:
- You don't need all of these. Just pick a few that interest you.
- [ ] [Great overview (video)](https://www.youtube.com/watch?v=-W9F__D3oY4)
- [ ] Short series:
- [Clones](http://www.lecloud.net/post/7295452622/scalability-for-dummies-part-1-clones)
- [Database](http://www.lecloud.net/post/7994751381/scalability-for-dummies-part-2-database)
- [Cache](http://www.lecloud.net/post/9246290032/scalability-for-dummies-part-3-cache)
- [Asynchronism](http://www.lecloud.net/post/9699762917/scalability-for-dummies-part-4-asynchronism)
- [ ] [Scalable Web Architecture and Distributed Systems](http://www.aosabook.org/en/distsys.html)
- [ ] [Fallacies of Distributed Computing Explained](https://pages.cs.wisc.edu/~zuyu/files/fallacies.pdf)
- [ ] [Jeff Dean - Building Software Systems At Google and Lessons Learned (video)](https://www.youtube.com/watch?v=modXC5IWTJI)
- [ ] [Introduction to Architecting Systems for Scale](http://lethain.com/introduction-to-architecting-systems-for-scale/)
- [ ] [Scaling mobile games to a global audience using App Engine and Cloud Datastore (video)](https://www.youtube.com/watch?v=9nWyWwY2Onc)
- [ ] [How Google Does Planet-Scale Engineering for Planet-Scale Infra (video)](https://www.youtube.com/watch?v=H4vMcD7zKM0)
- [ ] [The Importance of Algorithms](https://www.topcoder.com/community/competitive-programming/tutorials/the-importance-of-algorithms/)
- [ ] [Sharding](http://highscalability.com/blog/2009/8/6/an-unorthodox-approach-to-database-design-the-coming-of-the.html)
- [ ] [Engineering for the Long Game - Astrid Atkinson Keynote(video)](https://www.youtube.com/watch?v=p0jGmgIrf_M&list=PLRXxvay_m8gqVlExPC5DG3TGWJTaBgqSA&index=4)
- [ ] [7 Years Of YouTube Scalability Lessons In 30 Minutes](http://highscalability.com/blog/2012/3/26/7-years-of-youtube-scalability-lessons-in-30-minutes.html)
- [video](https://www.youtube.com/watch?v=G-lGCC4KKok)
- [ ] [How PayPal Scaled To Billions Of Transactions Daily Using Just 8VMs](http://highscalability.com/blog/2016/8/15/how-paypal-scaled-to-billions-of-transactions-daily-using-ju.html)
- [ ] [How to Remove Duplicates in Large Datasets](https://blog.clevertap.com/how-to-remove-duplicates-in-large-datasets/)
- [ ] [A look inside Etsy's scale and engineering culture with Jon Cowie (video)](https://www.youtube.com/watch?v=3vV4YiqKm1o)
- [ ] [What Led Amazon to its Own Microservices Architecture](http://thenewstack.io/led-amazon-microservices-architecture/)
- [ ] [To Compress Or Not To Compress, That Was Uber's Question](https://eng.uber.com/trip-data-squeeze/)
- [ ] [When Should Approximate Query Processing Be Used?](http://highscalability.com/blog/2016/2/25/when-should-approximate-query-processing-be-used.html)
- [ ] [Google's Transition From Single Datacenter, To Failover, To A Native Multihomed Architecture](http://highscalability.com/blog/2016/2/23/googles-transition-from-single-datacenter-to-failover-to-a-n.html)
- [ ] [The Image Optimization Technology That Serves Millions Of Requests Per Day](http://highscalability.com/blog/2016/6/15/the-image-optimization-technology-that-serves-millions-of-re.html)
- [ ] [A Patreon Architecture Short](http://highscalability.com/blog/2016/2/1/a-patreon-architecture-short.html)
- [ ] [Tinder: How Does One Of The Largest Recommendation Engines Decide Who You'll See Next?](http://highscalability.com/blog/2016/1/27/tinder-how-does-one-of-the-largest-recommendation-engines-de.html)
- [ ] [Design Of A Modern Cache](http://highscalability.com/blog/2016/1/25/design-of-a-modern-cache.html)
- [ ] [Live Video Streaming At Facebook Scale](http://highscalability.com/blog/2016/1/13/live-video-streaming-at-facebook-scale.html)
- [ ] [A Beginner's Guide To Scaling To 11 Million+ Users On Amazon's AWS](http://highscalability.com/blog/2016/1/11/a-beginners-guide-to-scaling-to-11-million-users-on-amazons.html)
- [ ] [A 360 Degree View Of The Entire Netflix Stack](http://highscalability.com/blog/2015/11/9/a-360-degree-view-of-the-entire-netflix-stack.html)
- [ ] [Latency Is Everywhere And It Costs You Sales - How To Crush It](http://highscalability.com/latency-everywhere-and-it-costs-you-sales-how-crush-it)
- [ ] [What Powers Instagram: Hundreds of Instances, Dozens of Technologies](http://instagram-engineering.tumblr.com/post/13649370142/what-powers-instagram-hundreds-of-instances)
- [ ] [Salesforce Architecture - How They Handle 1.3 Billion Transactions A Day](http://highscalability.com/blog/2013/9/23/salesforce-architecture-how-they-handle-13-billion-transacti.html)
- [ ] [ESPN's Architecture At Scale - Operating At 100,000 Duh Nuh Nuhs Per Second](http://highscalability.com/blog/2013/11/4/espns-architecture-at-scale-operating-at-100000-duh-nuh-nuhs.html)
- [ ] See "Messaging, Serialization, and Queueing Systems" way below for info on some of the technologies that can glue services together
- [ ] Twitter:
- [O'Reilly MySQL CE 2011: Jeremy Cole, "Big and Small Data at @Twitter" (video)](https://www.youtube.com/watch?v=5cKTP36HVgI)
- [Timelines at Scale](https://www.infoq.com/presentations/Twitter-Timeline-Scalability)
- For even more, see "Mining Massive Datasets" video series in the [Video Series](#video-series) section
- [ ] Practicing the system design process: Here are some ideas to try working through on paper, each with some documentation on how it was handled in the real world:
- review: [The System Design Primer](https://github.com/donnemartin/system-design-primer)
- [System Design from HiredInTech](http://www.hiredintech.com/system-design/)
- [cheat sheet](https://github.com/jwasham/coding-interview-university/blob/main/extras/cheat%20sheets/system-design.pdf)
- flow:
1. Understand the problem and scope:
- Define the use cases, with interviewer's help
- Suggest additional features
- Remove items that interviewer deems out of scope
- Assume high availability is required, add as a use case
2. Think about constraints:
- Ask how many requests per month
- Ask how many requests per second (they may volunteer it or make you do the math)
- Estimate reads vs. writes percentage
- Keep 80/20 rule in mind when estimating
- How much data written per second
- Total storage required over 5 years
- How much data read per second
3. Abstract design:
- Layers (service, data, caching)
- Infrastructure: load balancing, messaging
- Rough overview of any key algorithm that drives the service
- Consider bottlenecks and determine solutions
- Exercises:
- [Design a random unique ID generation system](https://blog.twitter.com/2010/announcing-snowflake)
- [Design a key-value database](http://www.slideshare.net/dvirsky/introduction-to-redis)
- [Design a picture sharing system](http://highscalability.com/blog/2011/12/6/instagram-architecture-14-million-users-terabytes-of-photos.html)
- [Design a recommendation system](http://ijcai13.org/files/tutorial_slides/td3.pdf)
- [Design a URL-shortener system: copied from above](http://www.hiredintech.com/system-design/the-system-design-process/)
- [Design a cache system](https://www.adayinthelifeof.nl/2011/02/06/memcache-internals/)
## Additional Learning
Добавих тези теми, за да Ви помогна да бъдете по-добри софтуерни инженери и да сте наясно с определени технологии и алгоритми, което ще разшири "инструментите", с които можете да работите
- ### Компилатори
- [Как работи един компилатор в ~1 минута (клип)](https://www.youtube.com/watch?v=IhC7sdYe-Jg)
- [Harvard CS50 - Компилатори (клип)](https://www.youtube.com/watch?v=CSZLNYF4Klo)
- [C++ (клип)](https://www.youtube.com/watch?v=twodd1KFfGk)
- [Да разберем оптимизирането на компилатори (C++) (клип)](https://www.youtube.com/watch?v=FnGCDLhaxKU)
- ### Emacs and vi(m)
- Запознайте се с някой unix-базиран кодов редактор
- vi(m):
- [Редактиране с vim 01 - Инсталация, настройване и различните режими (клип)](https://www.youtube.com/watch?v=5givLEMcINQ&index=1&list=PL13bz4SHGmRxlZVmWQ9DvXo1fEg4UdGkr)
- [VIM приключения](http://vim-adventures.com/)
- 4 клипа:
- [The vi/vim editor - Урок 1](https://www.youtube.com/watch?v=SI8TeVMX8pk)
- [The vi/vim editor - Урок 2](https://www.youtube.com/watch?v=F3OO7ZIOaJE)
- [The vi/vim editor - Урок 3](https://www.youtube.com/watch?v=ZYEccA_nMaI)
- [The vi/vim editor - Урок 4](https://www.youtube.com/watch?v=1lYD5gwgZIA)
- [Използване на Vi вместо Emacs](http://www.cs.yale.edu/homes/aspnes/classes/223/notes.html#Using_Vi_instead_of_Emacs)
- emacs:
- [Основите на Emacs (клип)](https://www.youtube.com/watch?v=hbmV1bnQ-i0)
- 3 клипа:
- [Emacs ръководство (За начинаещи) -Част 1- файлови команди, cut/copy/paste, cursor команди](https://www.youtube.com/watch?v=ujODL7MD04Q)
- [Emacs ръководство (За начинаещи) -Част 2- Управление на буфера, търсене, M-x grep и rgrep режими](https://www.youtube.com/watch?v=XWpsRupJ4II)
- [Emacs въководство (За начинаещи) -Част 3- Изрази, Твърдения, ~/.emacs файлове и пакети](https://www.youtube.com/watch?v=paSgzPso-yc)
- [Зъл режиим: Или как се научих да спра да се тревожа и да заобичам Emacs (клип)](https://www.youtube.com/watch?v=JWD1Fpdd4Pc)
- [Писане на C програми с Emacs](http://www.cs.yale.edu/homes/aspnes/classes/223/notes.html#Writing_C_programs_with_Emacs)
- [(по желание) Org режима в подробности: Управление на структурата (клип)](https://www.youtube.com/watch?v=nsGYet02bEk)
- ### Unix command line tools
- bash
- cat
- grep
- sed
- awk
- curl or wget
- sort
- tr
- uniq
- [strace](https://en.wikipedia.org/wiki/Strace)
- [tcpdump](https://danielmiessler.com/study/tcpdump/)
- ### Information theory (videos)
- [Khan Academy](https://www.khanacademy.org/computing/computer-science/informationtheory)
- Повече за Марковските процеси:
- [Основите на Марковския текст](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/waxgx/core-markov-text-generation)
- [Основите на имплементацията на Марковския текст](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/gZhiC/core-implementing-markov-text-generation)
- [Проект = Ръководство за Марковския текст](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/EUjrq/project-markov-text-generation-walk-through)
- Вижте повече в серията Information and Entropy MIT 6.050J надолу
- ### Паритет & код на Хаминг (клипове)
- [Въведение](https://www.youtube.com/watch?v=q-3BctoUpHE)
- [Паритет](https://www.youtube.com/watch?v=DdMcAUlxh1M)
- Код на Хаминг:
- [Откриване на грешки](https://www.youtube.com/watch?v=1A_NcXxdoCc)
- [Поправяне на грешки](https://www.youtube.com/watch?v=JAMLuxdHH8o)
- [Проверка за грешко](https://www.youtube.com/watch?v=wbH2VxzmoZk)
- ### Ентропия
- Вижте също клиповете надолу
- Първо изгледайте клиповете за information theory
- [Information Theory, Клод Шанън, Ентропия, Redundancy, Компресия на данни & Битове (клип)](https://youtu.be/JnJq3Py0dyM?t=176)
- ### Криптография
- Вижте също клиповете надолу
- Първо изгледайте клиповете за information theory
- [Khan Academy](https://www.khanacademy.org/computing/computer-science/cryptography)
- [Криптография: Функции за хеширане](https://www.youtube.com/watch?v=KqqOXndnvic&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=30)
- [Криптография: Криптиране](https://www.youtube.com/watch?v=9TNI2wHmaeI&index=31&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp)
- ### Компресия
- Първо изгледайте клиповете за information theory
- Computerphile (клипове):
- [Компресия](https://www.youtube.com/watch?v=Lto-ajuqW3w)
- [Ентропия в компресията](https://www.youtube.com/watch?v=M5c_RFKVkko)
- [Upside Down Trees (Дървета на Хъфман)](https://www.youtube.com/watch?v=umTbivyJoiI)
- [EXTRA BITS/TRITS - Дървета на Хъфман](https://www.youtube.com/watch?v=DV8efuB3h2g)
- [Елегантна компресия на текст (LZ 77 методът)](https://www.youtube.com/watch?v=goOa3DGezUA)
- [Компресията на текст среща вероятностите](https://www.youtube.com/watch?v=cCDCfoHTsaU)
- [Compressor Head клипове](https://www.youtube.com/playlist?list=PLOU2XLYxmsIJGErt5rrCqaSGTMyyqNt2H)
- [(по желание) Google Developers Live: GZIP не е достатъчен!](https://www.youtube.com/watch?v=whGwm0Lky2s)
- ### Компютърна сигурност
- [MIT (23 клипа)](https://www.youtube.com/playlist?list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh)
- [Introduction, Threat Models](https://www.youtube.com/watch?v=GqmQg-cszw4&index=1&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh)
- [Control Hijacking Attacks](https://www.youtube.com/watch?v=6bwzNg5qQ0o&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh&index=2)
- [Buffer Overflow Exploits and Defenses](https://www.youtube.com/watch?v=drQyrzRoRiA&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh&index=3)
- [Privilege Separation](https://www.youtube.com/watch?v=6SIJmoE9L9g&index=4&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh)
- [Capabilities](https://www.youtube.com/watch?v=8VqTSY-11F4&index=5&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh)
- [Sandboxing Native Code](https://www.youtube.com/watch?v=VEV74hwASeU&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh&index=6)
- [Web Security Model](https://www.youtube.com/watch?v=chkFBigodIw&index=7&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh)
- [Securing Web Applications](https://www.youtube.com/watch?v=EBQIGy1ROLY&index=8&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh)
- [Symbolic Execution](https://www.youtube.com/watch?v=yRVZPvHYHzw&index=9&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh)
- [Network Security](https://www.youtube.com/watch?v=SIEVvk3NVuk&index=11&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh)
- [Network Protocols](https://www.youtube.com/watch?v=QOtA76ga_fY&index=12&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh)
- [Side-Channel Attacks](https://www.youtube.com/watch?v=PuVMkSEcPiI&index=15&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh)
- ### Garbage collection
- [GC in Python (video)](https://www.youtube.com/watch?v=iHVs_HkjdmI)
- [Deep Dive Java: Garbage Collection is Good!](https://www.infoq.com/presentations/garbage-collection-benefits)
- [Deep Dive Python: Garbage Collection in CPython (video)](https://www.youtube.com/watch?v=P-8Z0-MhdQs&list=PLdzf4Clw0VbOEWOS_sLhT_9zaiQDrS5AR&index=3)
- ### Parallel Programming
- [Coursera (Scala)](https://www.coursera.org/learn/parprog1/home/week/1)
- [Efficient Python for High Performance Parallel Computing (video)](https://www.youtube.com/watch?v=uY85GkaYzBk)
- ### Messaging, Serialization, and Queueing Systems
- [Thrift](https://thrift.apache.org/)
- [Tutorial](http://thrift-tutorial.readthedocs.io/en/latest/intro.html)
- [Protocol Buffers](https://developers.google.com/protocol-buffers/)
- [Tutorials](https://developers.google.com/protocol-buffers/docs/tutorials)
- [gRPC](http://www.grpc.io/)
- [gRPC 101 for Java Developers (video)](https://www.youtube.com/watch?v=5tmPvSe7xXQ&list=PLcTqM9n_dieN0k1nSeN36Z_ppKnvMJoly&index=1)
- [Redis](http://redis.io/)
- [Tutorial](http://try.redis.io/)
- [Amazon SQS (queue)](https://aws.amazon.com/sqs/)
- [Amazon SNS (pub-sub)](https://aws.amazon.com/sns/)
- [RabbitMQ](https://www.rabbitmq.com/)
- [Get Started](https://www.rabbitmq.com/getstarted.html)
- [Celery](http://www.celeryproject.org/)
- [First Steps With Celery](http://docs.celeryproject.org/en/latest/getting-started/first-steps-with-celery.html)
- [ZeroMQ](http://zeromq.org/)
- [Intro - Read The Manual](http://zeromq.org/intro:read-the-manual)
- [ActiveMQ](http://activemq.apache.org/)
- [Kafka](http://kafka.apache.org/documentation.html#introduction)
- [MessagePack](http://msgpack.org/index.html)
- [Avro](https://avro.apache.org/)
- ### A\*
- [A Search Algorithm](https://en.wikipedia.org/wiki/A*_search_algorithm)
- [A\* Pathfinding Tutorial (video)](https://www.youtube.com/watch?v=KNXfSOx4eEE)
- [A\* Pathfinding (E01: algorithm explanation) (video)](https://www.youtube.com/watch?v=-L-WgKMFuhE)
- ### Fast Fourier Transform
- [An Interactive Guide To The Fourier Transform](https://betterexplained.com/articles/an-interactive-guide-to-the-fourier-transform/)
- [What is a Fourier transform? What is it used for?](http://www.askamathematician.com/2012/09/q-what-is-a-fourier-transform-what-is-it-used-for/)
- [What is the Fourier Transform? (video)](https://www.youtube.com/watch?v=Xxut2PN-V8Q)
- [Divide & Conquer: FFT (video)](https://www.youtube.com/watch?v=iTMn0Kt18tg&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=4)
- [Understanding The FFT](http://jakevdp.github.io/blog/2013/08/28/understanding-the-fft/)
- ### Bloom Filter
- Given a Bloom filter with m bits and k hashing functions, both insertion and membership testing are O(k)
- [Bloom Filters (video)](https://www.youtube.com/watch?v=-SuTGoFYjZs)
- [Bloom Filters | Mining of Massive Datasets | Stanford University (video)](https://www.youtube.com/watch?v=qBTdukbzc78)
- [Tutorial](http://billmill.org/bloomfilter-tutorial/)
- [How To Write A Bloom Filter App](http://blog.michaelschmatz.com/2016/04/11/how-to-write-a-bloom-filter-cpp/)
- ### HyperLogLog
- [How To Count A Billion Distinct Objects Using Only 1.5KB Of Memory](http://highscalability.com/blog/2012/4/5/big-data-counting-how-to-count-a-billion-distinct-objects-us.html)
- ### Locality-Sensitive Hashing
- Used to determine the similarity of documents
- The opposite of MD5 or SHA which are used to determine if 2 documents/strings are exactly the same
- [Simhashing (hopefully) made simple](http://ferd.ca/simhashing-hopefully-made-simple.html)
- ### van Emde Boas Trees
- [Divide & Conquer: van Emde Boas Trees (video)](https://www.youtube.com/watch?v=hmReJCupbNU&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=6)
- [MIT Lecture Notes](https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-046j-design-and-analysis-of-algorithms-spring-2012/lecture-notes/MIT6_046JS12_lec15.pdf)
- ### Augmented Data Structures
- [CS 61B Lecture 39: Augmenting Data Structures](https://archive.org/details/ucberkeley_webcast_zksIj9O8_jc)
- ### Balanced search trees
- Know at least one type of balanced binary tree (and know how it's implemented):
- "Among balanced search trees, AVL and 2/3 trees are now passé, and red-black trees seem to be more popular.
A particularly interesting self-organizing data structure is the splay tree, which uses rotations
to move any accessed key to the root." - Skiena
- Of these, I chose to implement a splay tree. From what I've read, you won't implement a
balanced search tree in your interview. But I wanted exposure to coding one up
and let's face it, splay trees are the bee's knees. I did read a lot of red-black tree code
- Splay tree: insert, search, delete functions
If you end up implementing red/black tree try just these:
- Search and insertion functions, skipping delete
- I want to learn more about B-Tree since it's used so widely with very large data sets
- [Self-balancing binary search tree](https://en.wikipedia.org/wiki/Self-balancing_binary_search_tree)
- **AVL trees**
- In practice:
From what I can tell, these aren't used much in practice, but I could see where they would be:
The AVL tree is another structure supporting O(log n) search, insertion, and removal. It is more rigidly
balanced than red–black trees, leading to slower insertion and removal but faster retrieval. This makes it
attractive for data structures that may be built once and loaded without reconstruction, such as language
dictionaries (or program dictionaries, such as the opcodes of an assembler or interpreter)
- [MIT AVL Trees / AVL Sort (video)](https://www.youtube.com/watch?v=FNeL18KsWPc&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=6)
- [AVL Trees (video)](https://www.coursera.org/learn/data-structures/lecture/Qq5E0/avl-trees)
- [AVL Tree Implementation (video)](https://www.coursera.org/learn/data-structures/lecture/PKEBC/avl-tree-implementation)
- [Split And Merge](https://www.coursera.org/learn/data-structures/lecture/22BgE/split-and-merge)
- **Splay trees**
- In practice:
Splay trees are typically used in the implementation of caches, memory allocators, routers, garbage collectors,
data compression, ropes (replacement of string used for long text strings), in Windows NT (in the virtual memory,
networking and file system code) etc
- [CS 61B: Splay Trees (video)](https://archive.org/details/ucberkeley_webcast_G5QIXywcJlY)
- MIT Lecture: Splay Trees:
- Gets very mathy, but watch the last 10 minutes for sure.
- [Video](https://www.youtube.com/watch?v=QnPl_Y6EqMo)
- **Red/black trees**
- These are a translation of a 2-3 tree (see below).
- In practice:
Red–black trees offer worst-case guarantees for insertion time, deletion time, and search time.
Not only does this make them valuable in time-sensitive applications such as real-time applications,
but it makes them valuable building blocks in other data structures which provide worst-case guarantees;
for example, many data structures used in computational geometry can be based on red–black trees, and
the Completely Fair Scheduler used in current Linux kernels uses red–black trees. In the version 8 of Java,
the Collection HashMap has been modified such that instead of using a LinkedList to store identical elements with poor
hashcodes, a Red-Black tree is used
- [Aduni - Algorithms - Lecture 4 (link jumps to starting point) (video)](https://youtu.be/1W3x0f_RmUo?list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&t=3871)
- [Aduni - Algorithms - Lecture 5 (video)](https://www.youtube.com/watch?v=hm2GHwyKF1o&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&index=5)
- [Red-Black Tree](https://en.wikipedia.org/wiki/Red%E2%80%93black_tree)
- [An Introduction To Binary Search And Red Black Tree](https://www.topcoder.com/community/competitive-programming/tutorials/an-introduction-to-binary-search-and-red-black-trees/)
- **2-3 search trees**
- In practice:
2-3 trees have faster inserts at the expense of slower searches (since height is more compared to AVL trees).
- You would use 2-3 tree very rarely because its implementation involves different types of nodes. Instead, people use Red Black trees.
- [23-Tree Intuition and Definition (video)](https://www.youtube.com/watch?v=C3SsdUqasD4&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6&index=2)
- [Binary View of 23-Tree](https://www.youtube.com/watch?v=iYvBtGKsqSg&index=3&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6)
- [2-3 Trees (student recitation) (video)](https://www.youtube.com/watch?v=TOb1tuEZ2X4&index=5&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp)
- **2-3-4 Trees (aka 2-4 trees)**
- In practice:
For every 2-4 tree, there are corresponding red–black trees with data elements in the same order. The insertion and deletion
operations on 2-4 trees are also equivalent to color-flipping and rotations in red–black trees. This makes 2-4 trees an
important tool for understanding the logic behind red–black trees, and this is why many introductory algorithm texts introduce
2-4 trees just before red–black trees, even though **2-4 trees are not often used in practice**.
- [CS 61B Lecture 26: Balanced Search Trees (video)](https://archive.org/details/ucberkeley_webcast_zqrqYXkth6Q)
- [Bottom Up 234-Trees (video)](https://www.youtube.com/watch?v=DQdMYevEyE4&index=4&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6)
- [Top Down 234-Trees (video)](https://www.youtube.com/watch?v=2679VQ26Fp4&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6&index=5)
- **N-ary (K-ary, M-ary) trees**
- note: the N or K is the branching factor (max branches)
- binary trees are a 2-ary tree, with branching factor = 2
- 2-3 trees are 3-ary
- [K-Ary Tree](https://en.wikipedia.org/wiki/K-ary_tree)
- **B-Trees**
- Fun fact: it's a mystery, but the B could stand for Boeing, Balanced, or Bayer (co-inventor).
- In Practice:
B-Trees are widely used in databases. Most modern filesystems use B-trees (or Variants). In addition to
its use in databases, the B-tree is also used in filesystems to allow quick random access to an arbitrary
block in a particular file. The basic problem is turning the file block i address into a disk block
(or perhaps to a cylinder-head-sector) address
- [B-Tree](https://en.wikipedia.org/wiki/B-tree)
- [B-Tree Datastructure](http://btechsmartclass.com/data_structures/b-trees.html)
- [Introduction to B-Trees (video)](https://www.youtube.com/watch?v=I22wEC1tTGo&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6&index=6)
- [B-Tree Definition and Insertion (video)](https://www.youtube.com/watch?v=s3bCdZGrgpA&index=7&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6)
- [B-Tree Deletion (video)](https://www.youtube.com/watch?v=svfnVhJOfMc&index=8&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6)
- [MIT 6.851 - Memory Hierarchy Models (video)](https://www.youtube.com/watch?v=V3omVLzI0WE&index=7&list=PLUl4u3cNGP61hsJNdULdudlRL493b-XZf) - covers cache-oblivious B-Trees, very interesting data structures - the first 37 minutes are very technical, may be skipped (B is block size, cache line size)
- ### k-D Trees
- Great for finding number of points in a rectangle or higher dimension object
- A good fit for k-nearest neighbors
- [Kd Trees (video)](https://www.youtube.com/watch?v=W94M9D_yXKk)
- [kNN K-d tree algorithm (video)](https://www.youtube.com/watch?v=Y4ZgLlDfKDg)
- ### Skip lists
- "These are somewhat of a cult data structure" - Skiena
- [Randomization: Skip Lists (video)](https://www.youtube.com/watch?v=2g9OSRKJuzM&index=10&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp)
- [For animations and a little more detail](https://en.wikipedia.org/wiki/Skip_list)
- ### Network Flows
- [Ford-Fulkerson in 5 minutes — Step by step example (video)](https://www.youtube.com/watch?v=Tl90tNtKvxs)
- [Ford-Fulkerson Algorithm (video)](https://www.youtube.com/watch?v=v1VgJmkEJW0)
- [Network Flows (video)](https://www.youtube.com/watch?v=2vhN4Ice5jI)
- ### Disjoint Sets & Union Find
- [UCB 61B - Disjoint Sets; Sorting & selection (video)](https://archive.org/details/ucberkeley_webcast_MAEGXTwmUsI)
- [Sedgewick Algorithms - Union-Find (6 videos)](https://www.coursera.org/learn/algorithms-part1/home/week/1)
- ### Math for Fast Processing
- [Integer Arithmetic, Karatsuba Multiplication (video)](https://www.youtube.com/watch?v=eCaXlAaN2uE&index=11&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb)
- [The Chinese Remainder Theorem (used in cryptography) (video)](https://www.youtube.com/watch?v=ru7mWZJlRQg)
- ### Treap
- Combination of a binary search tree and a heap
- [Treap](https://en.wikipedia.org/wiki/Treap)
- [Data Structures: Treaps explained (video)](https://www.youtube.com/watch?v=6podLUYinH8)
- [Applications in set operations](https://www.cs.cmu.edu/~scandal/papers/treaps-spaa98.pdf)
- ### Linear Programming (videos)
- [Linear Programming](https://www.youtube.com/watch?v=M4K6HYLHREQ)
- [Finding minimum cost](https://www.youtube.com/watch?v=2ACJ9ewUC6U)
- [Finding maximum value](https://www.youtube.com/watch?v=8AA_81xI3ik)
- [Solve Linear Equations with Python - Simplex Algorithm](https://www.youtube.com/watch?v=44pAWI7v5Zk)
- ### Geometry, Convex hull (videos)
- [Graph Alg. IV: Intro to geometric algorithms - Lecture 9](https://youtu.be/XIAQRlNkJAw?list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&t=3164)
- [Geometric Algorithms: Graham & Jarvis - Lecture 10](https://www.youtube.com/watch?v=J5aJEcOr6Eo&index=10&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm)
- [Divide & Conquer: Convex Hull, Median Finding](https://www.youtube.com/watch?v=EzeYI7p9MjU&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=2)
- ### Discrete math
- [Computer Science 70, 001 - Spring 2015 - Discrete Mathematics and Probability Theory](http://www.infocobuild.com/education/audio-video-courses/computer-science/cs70-spring2015-berkeley.html)
- [Discrete Mathematics by Shai Simonson (19 videos)](https://www.youtube.com/playlist?list=PLWX710qNZo_sNlSWRMVIh6kfTjolNaZ8t)
- [Discrete Mathematics By IIT Ropar NPTEL](https://nptel.ac.in/courses/106/106/106106183/)
- ### Machine Learning
- Why ML?
- [How Google Is Remaking Itself As A Machine Learning First Company](https://backchannel.com/how-google-is-remaking-itself-as-a-machine-learning-first-company-ada63defcb70)
- [Large-Scale Deep Learning for Intelligent Computer Systems (video)](https://www.youtube.com/watch?v=QSaZGT4-6EY)
- [Deep Learning and Understandability versus Software Engineering and Verification by Peter Norvig](https://www.youtube.com/watch?v=X769cyzBNVw)
- [Google's Cloud Machine learning tools (video)](https://www.youtube.com/watch?v=Ja2hxBAwG_0)
- [Google Developers' Machine Learning Recipes (Scikit Learn & Tensorflow) (video)](https://www.youtube.com/playlist?list=PLOU2XLYxmsIIuiBfYad6rFYQU_jL2ryal)
- [Tensorflow (video)](https://www.youtube.com/watch?v=oZikw5k_2FM)
- [Tensorflow Tutorials](https://www.tensorflow.org/versions/r0.11/tutorials/index.html)
- [Practical Guide to implementing Neural Networks in Python (using Theano)](http://www.analyticsvidhya.com/blog/2016/04/neural-networks-python-theano/)
- Courses:
- [Great starter course: Machine Learning](https://www.coursera.org/learn/machine-learning) - [videos only](https://www.youtube.com/playlist?list=PLZ9qNFMHZ-A4rycgrgOYma6zxF4BZGGPW) - see videos 12-18 for a review of linear algebra (14 and 15 are duplicates)
- [Neural Networks for Machine Learning](https://www.coursera.org/learn/neural-networks)
- [Google's Deep Learning Nanodegree](https://www.udacity.com/course/deep-learning--ud730)
- [Google/Kaggle Machine Learning Engineer Nanodegree](https://www.udacity.com/course/machine-learning-engineer-nanodegree-by-google--nd009)
- [Self-Driving Car Engineer Nanodegree](https://www.udacity.com/drive)
- [Metis Online Course ($99 for 2 months)](http://www.thisismetis.com/explore-data-science)
- Resources:
- Books:
- [Python Machine Learning](https://www.amazon.com/Python-Machine-Learning-Sebastian-Raschka/dp/1783555130/)
- [Data Science from Scratch: First Principles with Python](https://www.amazon.com/Data-Science-Scratch-Principles-Python/dp/149190142X)
- [Introduction to Machine Learning with Python](https://www.amazon.com/Introduction-Machine-Learning-Python-Scientists/dp/1449369413/)
- [Machine Learning for Software Engineers](https://github.com/ZuzooVn/machine-learning-for-software-engineers)
- Data School: http://www.dataschool.io/
---
## Additional Detail on Some Subjects
I added these to reinforce some ideas already presented above, but didn't want to include them
above because it's just too much. It's easy to overdo it on a subject.
You want to get hired in this century, right?
- **SOLID**
- [ ] [Bob Martin SOLID Principles of Object Oriented and Agile Design (video)](https://www.youtube.com/watch?v=TMuno5RZNeE)
- [ ] S - [Single Responsibility Principle](http://www.oodesign.com/single-responsibility-principle.html) | [Single responsibility to each Object](http://www.javacodegeeks.com/2011/11/solid-single-responsibility-principle.html)
- [more flavor](https://docs.google.com/open?id=0ByOwmqah_nuGNHEtcU5OekdDMkk)
- [ ] O - [Open/Closed Principle](http://www.oodesign.com/open-close-principle.html) | [On production level Objects are ready for extension but not for modification](https://en.wikipedia.org/wiki/Open/closed_principle)
- [more flavor](http://docs.google.com/a/cleancoder.com/viewer?a=v&pid=explorer&chrome=true&srcid=0BwhCYaYDn8EgN2M5MTkwM2EtNWFkZC00ZTI3LWFjZTUtNTFhZGZiYmUzODc1&hl=en)
- [ ] L - [Liskov Substitution Principle](http://www.oodesign.com/liskov-s-substitution-principle.html) | [Base Class and Derived class follow ‘IS A’ Principle](http://stackoverflow.com/questions/56860/what-is-the-liskov-substitution-principle)
- [more flavor](http://docs.google.com/a/cleancoder.com/viewer?a=v&pid=explorer&chrome=true&srcid=0BwhCYaYDn8EgNzAzZjA5ZmItNjU3NS00MzQ5LTkwYjMtMDJhNDU5ZTM0MTlh&hl=en)
- [ ] I - [Interface segregation principle](http://www.oodesign.com/interface-segregation-principle.html) | clients should not be forced to implement interfaces they don't use
- [Interface Segregation Principle in 5 minutes (video)](https://www.youtube.com/watch?v=3CtAfl7aXAQ)
- [more flavor](http://docs.google.com/a/cleancoder.com/viewer?a=v&pid=explorer&chrome=true&srcid=0BwhCYaYDn8EgOTViYjJhYzMtMzYxMC00MzFjLWJjMzYtOGJiMDc5N2JkYmJi&hl=en)
- [ ] D -[Dependency Inversion principle](http://www.oodesign.com/dependency-inversion-principle.html) | Reduce the dependency In composition of objects.
- [Why Is The Dependency Inversion Principle And Why Is It Important](http://stackoverflow.com/questions/62539/what-is-the-dependency-inversion-principle-and-why-is-it-important)
- [more flavor](http://docs.google.com/a/cleancoder.com/viewer?a=v&pid=explorer&chrome=true&srcid=0BwhCYaYDn8EgMjdlMWIzNGUtZTQ0NC00ZjQ5LTkwYzQtZjRhMDRlNTQ3ZGMz&hl=en)
- **Union-Find**
- [Overview](https://www.coursera.org/learn/data-structures/lecture/JssSY/overview)
- [Naive Implementation](https://www.coursera.org/learn/data-structures/lecture/EM5D0/naive-implementations)
- [Trees](https://www.coursera.org/learn/data-structures/lecture/Mxu0w/trees)
- [Union By Rank](https://www.coursera.org/learn/data-structures/lecture/qb4c2/union-by-rank)
- [Path Compression](https://www.coursera.org/learn/data-structures/lecture/Q9CVI/path-compression)
- [Analysis Options](https://www.coursera.org/learn/data-structures/lecture/GQQLN/analysis-optional)
- **More Dynamic Programming** (videos)
- [6.006: Dynamic Programming I: Fibonacci, Shortest Paths](https://www.youtube.com/watch?v=OQ5jsbhAv_M&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=19)
- [6.006: Dynamic Programming II: Text Justification, Blackjack](https://www.youtube.com/watch?v=ENyox7kNKeY&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=20)
- [6.006: DP III: Parenthesization, Edit Distance, Knapsack](https://www.youtube.com/watch?v=ocZMDMZwhCY&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=21)
- [6.006: DP IV: Guitar Fingering, Tetris, Super Mario Bros.](https://www.youtube.com/watch?v=tp4_UXaVyx8&index=22&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb)
- [6.046: Dynamic Programming & Advanced DP](https://www.youtube.com/watch?v=Tw1k46ywN6E&index=14&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp)
- [6.046: Dynamic Programming: All-Pairs Shortest Paths](https://www.youtube.com/watch?v=NzgFUwOaoIw&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=15)
- [6.046: Dynamic Programming (student recitation)](https://www.youtube.com/watch?v=krZI60lKPek&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=12)
- **Advanced Graph Processing** (videos)
- [Synchronous Distributed Algorithms: Symmetry-Breaking. Shortest-Paths Spanning Trees](https://www.youtube.com/watch?v=mUBmcbbJNf4&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=27)
- [Asynchronous Distributed Algorithms: Shortest-Paths Spanning Trees](https://www.youtube.com/watch?v=kQ-UQAzcnzA&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=28)
- MIT **Probability** (mathy, and go slowly, which is good for mathy things) (videos):
- [MIT 6.042J - Probability Introduction](https://www.youtube.com/watch?v=SmFwFdESMHI&index=18&list=PLB7540DEDD482705B)
- [MIT 6.042J - Conditional Probability](https://www.youtube.com/watch?v=E6FbvM-FGZ8&index=19&list=PLB7540DEDD482705B)
- [MIT 6.042J - Independence](https://www.youtube.com/watch?v=l1BCv3qqW4A&index=20&list=PLB7540DEDD482705B)
- [MIT 6.042J - Random Variables](https://www.youtube.com/watch?v=MOfhhFaQdjw&list=PLB7540DEDD482705B&index=21)
- [MIT 6.042J - Expectation I](https://www.youtube.com/watch?v=gGlMSe7uEkA&index=22&list=PLB7540DEDD482705B)
- [MIT 6.042J - Expectation II](https://www.youtube.com/watch?v=oI9fMUqgfxY&index=23&list=PLB7540DEDD482705B)
- [MIT 6.042J - Large Deviations](https://www.youtube.com/watch?v=q4mwO2qS2z4&index=24&list=PLB7540DEDD482705B)
- [MIT 6.042J - Random Walks](https://www.youtube.com/watch?v=56iFMY8QW2k&list=PLB7540DEDD482705B&index=25)
- [Simonson: Approximation Algorithms (video)](https://www.youtube.com/watch?v=oDniZCmNmNw&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&index=19)
- **String Matching**
- Rabin-Karp (videos):
- [Rabin Karps Algorithm](https://www.coursera.org/learn/data-structures/lecture/c0Qkw/rabin-karps-algorithm)
- [Precomputing](https://www.coursera.org/learn/data-structures/lecture/nYrc8/optimization-precomputation)
- [Optimization: Implementation and Analysis](https://www.coursera.org/learn/data-structures/lecture/h4ZLc/optimization-implementation-and-analysis)
- [Table Doubling, Karp-Rabin](https://www.youtube.com/watch?v=BRO7mVIFt08&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=9)
- [Rolling Hashes, Amortized Analysis](https://www.youtube.com/watch?v=w6nuXg0BISo&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=32)
- Knuth-Morris-Pratt (KMP):
- [TThe Knuth-Morris-Pratt (KMP) String Matching Algorithm](https://www.youtube.com/watch?v=5i7oKodCRJo)
- Boyer–Moore string search algorithm
- [Boyer-Moore String Search Algorithm](https://en.wikipedia.org/wiki/Boyer%E2%80%93Moore_string_search_algorithm)
- [Advanced String Searching Boyer-Moore-Horspool Algorithms (video)](https://www.youtube.com/watch?v=QDZpzctPf10)
- [Coursera: Algorithms on Strings](https://www.coursera.org/learn/algorithms-on-strings/home/week/1)
- starts off great, but by the time it gets past KMP it gets more complicated than it needs to be
- nice explanation of tries
- can be skipped
- **Sorting**
- Stanford lectures on sorting:
- [Lecture 15 | Programming Abstractions (video)](https://www.youtube.com/watch?v=ENp00xylP7c&index=15&list=PLFE6E58F856038C69)
- [Lecture 16 | Programming Abstractions (video)](https://www.youtube.com/watch?v=y4M9IVgrVKo&index=16&list=PLFE6E58F856038C69)
- Shai Simonson, [Aduni.org](http://www.aduni.org/):
- [Algorithms - Sorting - Lecture 2 (video)](https://www.youtube.com/watch?v=odNJmw5TOEE&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&index=2)
- [Algorithms - Sorting II - Lecture 3 (video)](https://www.youtube.com/watch?v=hj8YKFTFKEE&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&index=3)
- Steven Skiena lectures on sorting:
- [lecture begins at 26:46 (video)](https://youtu.be/ute-pmMkyuk?list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&t=1600)
- [lecture begins at 27:40 (video)](https://www.youtube.com/watch?v=yLvp-pB8mak&index=8&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b)
- [lecture begins at 35:00 (video)](https://www.youtube.com/watch?v=q7K9otnzlfE&index=9&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b)
- [lecture begins at 23:50 (video)](https://www.youtube.com/watch?v=TvqIGu9Iupw&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&index=10)
## Video Series
Sit back and enjoy.
- [List of individual Dynamic Programming problems (each is short)](https://www.youtube.com/playlist?list=PLrmLmBdmIlpsHaNTPP_jHHDx_os9ItYXr)
- [x86 Architecture, Assembly, Applications (11 videos)](https://www.youtube.com/playlist?list=PL038BE01D3BAEFDB0)
- [MIT 18.06 Linear Algebra, Spring 2005 (35 videos)](https://www.youtube.com/playlist?list=PLE7DDD91010BC51F8)
- [Excellent - MIT Calculus Revisited: Single Variable Calculus](https://www.youtube.com/playlist?list=PL3B08AE665AB9002A)
- CSE373 - Analysis of Algorithms (25 videos)
- [Skiena lectures from Algorithm Design Manual](https://www.youtube.com/watch?v=ZFjhkohHdAA&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&index=1)
- [UC Berkeley 61B (Spring 2014): Data Structures (25 videos)](https://archive.org/details/ucberkeley-webcast-PL-XXv-cvA_iAlnI-BQr9hjqADPBtujFJd)
- [UC Berkeley 61B (Fall 2006): Data Structures (39 videos)](https://archive.org/details/ucberkeley-webcast-PL4BBB74C7D2A1049C)
- [UC Berkeley 61C: Machine Structures (26 videos)](https://archive.org/details/ucberkeley-webcast-PL-XXv-cvA_iCl2-D-FS5mk0jFF6cYSJs_)
- [OOSE: Software Dev Using UML and Java (21 videos)](https://www.youtube.com/playlist?list=PLJ9pm_Rc9HesnkwKlal_buSIHA-jTZMpO)
- ~~[UC Berkeley CS 152: Computer Architecture and Engineering (20 videos)](https://www.youtube.com/watch?v=UH0QYvtP7Rk&index=20&list=PLkFD6_40KJIwEiwQx1dACXwh-2Fuo32qr)~~
- [MIT 6.004: Computation Structures (49 videos)](https://www.youtube.com/playlist?list=PLDSlqjcPpoL64CJdF0Qee5oWqGS6we_Yu)
- [Carnegie Mellon - Computer Architecture Lectures (39 videos)](https://www.youtube.com/playlist?list=PL5PHm2jkkXmi5CxxI7b3JCL1TWybTDtKq)
- [MIT 6.006: Intro to Algorithms (47 videos)](https://www.youtube.com/watch?v=HtSuA80QTyo&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&nohtml5=False)
- [MIT 6.033: Computer System Engineering (22 videos)](https://www.youtube.com/watch?v=zm2VP0kHl1M&list=PL6535748F59DCA484)
- [MIT 6.034 Artificial Intelligence, Fall 2010 (30 videos)](https://www.youtube.com/playlist?list=PLUl4u3cNGP63gFHB6xb-kVBiQHYe_4hSi)
- [MIT 6.042J: Mathematics for Computer Science, Fall 2010 (25 videos)](https://www.youtube.com/watch?v=L3LMbpZIKhQ&list=PLB7540DEDD482705B)
- [MIT 6.046: Design and Analysis of Algorithms (34 videos)](https://www.youtube.com/watch?v=2P-yW7LQr08&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp)
- [MIT 6.050J: Information and Entropy, Spring 2008 (19 videos)](https://www.youtube.com/watch?v=phxsQrZQupo&list=PL_2Bwul6T-A7OldmhGODImZL8KEVE38X7)
- [MIT 6.824: Distributed Systems, Spring 2020 (20 videos)](https://www.youtube.com/watch?v=cQP8WApzIQQ&list=PLrw6a1wE39_tb2fErI4-WkMbsvGQk9_UB)
- [MIT 6.851: Advanced Data Structures (22 videos)](https://www.youtube.com/watch?v=T0yzrZL1py0&list=PLUl4u3cNGP61hsJNdULdudlRL493b-XZf&index=1)
- [MIT 6.854: Advanced Algorithms, Spring 2016 (24 videos)](https://www.youtube.com/playlist?list=PL6ogFv-ieghdoGKGg2Bik3Gl1glBTEu8c)
- [Harvard COMPSCI 224: Advanced Algorithms (25 videos)](https://www.youtube.com/playlist?list=PL2SOU6wwxB0uP4rJgf5ayhHWgw7akUWSf)
- [MIT 6.858 Computer Systems Security, Fall 2014](https://www.youtube.com/watch?v=GqmQg-cszw4&index=1&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh)
- [Stanford: Programming Paradigms (27 videos)](https://www.youtube.com/playlist?list=PL9D558D49CA734A02)
- [Introduction to Cryptography by Christof Paar](https://www.youtube.com/playlist?list=PL6N5qY2nvvJE8X75VkXglSrVhLv1tVcfy)
- [Course Website along with Slides and Problem Sets](http://www.crypto-textbook.com/)
- [Mining Massive Datasets - Stanford University (94 videos)](https://www.youtube.com/playlist?list=PLLssT5z_DsK9JDLcT8T62VtzwyW9LNepV)
- [Graph Theory by Sarada Herke (67 videos)](https://www.youtube.com/user/DrSaradaHerke/playlists?shelf_id=5&view=50&sort=dd)
## Computer Science Courses
- [Directory of Online CS Courses](https://github.com/open-source-society/computer-science)
- [Directory of CS Courses (many with online lectures)](https://github.com/prakhar1989/awesome-courses)
## Algorithms implementation
- [Multiple Algorithms implementation by Princeton University](https://algs4.cs.princeton.edu/code)
## Papers
- [Love classic papers?](https://www.cs.cmu.edu/~crary/819-f09/)
- [1978: Communicating Sequential Processes](http://spinroot.com/courses/summer/Papers/hoare_1978.pdf)
- [implemented in Go](https://godoc.org/github.com/thomas11/csp)
- [2003: The Google File System](http://static.googleusercontent.com/media/research.google.com/en//archive/gfs-sosp2003.pdf)
- replaced by Colossus in 2012
- [2004: MapReduce: Simplified Data Processing on Large Clusters](http://static.googleusercontent.com/media/research.google.com/en//archive/mapreduce-osdi04.pdf)
- mostly replaced by Cloud Dataflow?
- [2006: Bigtable: A Distributed Storage System for Structured Data](https://static.googleusercontent.com/media/research.google.com/en//archive/bigtable-osdi06.pdf)
- [2006: The Chubby Lock Service for Loosely-Coupled Distributed Systems](https://research.google.com/archive/chubby-osdi06.pdf)
- [2007: Dynamo: Amazon’s Highly Available Key-value Store](http://s3.amazonaws.com/AllThingsDistributed/sosp/amazon-dynamo-sosp2007.pdf)
- The Dynamo paper kicked off the NoSQL revolution
- [2007: What Every Programmer Should Know About Memory (very long, and the author encourages skipping of some sections)](https://www.akkadia.org/drepper/cpumemory.pdf)
- 2012: AddressSanitizer: A Fast Address Sanity Checker:
- [paper](http://static.googleusercontent.com/media/research.google.com/en//pubs/archive/37752.pdf)
- [video](https://www.usenix.org/conference/atc12/technical-sessions/presentation/serebryany)
- 2013: Spanner: Google’s Globally-Distributed Database:
- [paper](http://static.googleusercontent.com/media/research.google.com/en//archive/spanner-osdi2012.pdf)
- [video](https://www.usenix.org/node/170855)
- [2014: Machine Learning: The High-Interest Credit Card of Technical Debt](http://static.googleusercontent.com/media/research.google.com/en//pubs/archive/43146.pdf)
- [2015: Continuous Pipelines at Google](http://static.googleusercontent.com/media/research.google.com/en//pubs/archive/43790.pdf)
- [2015: High-Availability at Massive Scale: Building Google’s Data Infrastructure for Ads](https://static.googleusercontent.com/media/research.google.com/en//pubs/archive/44686.pdf)
- [2015: TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems](http://download.tensorflow.org/paper/whitepaper2015.pdf)
- [2015: How Developers Search for Code: A Case Study](http://static.googleusercontent.com/media/research.google.com/en//pubs/archive/43835.pdf)
- More papers: [1,000 papers](https://github.com/0voice/computer_expert_paper)
## LICENSE
[CC-BY-SA-4.0](./LICENSE.txt)