Added the big list.

2016-06-05 19:46:49 -07:00
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 # Project 9894
-TBD
+This is a setup for this project, which is stealthy right now. Will add more detail soon.
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 ##########################################################################################
 ##  Knowledge:
 ##########################################################################################
 * - Computer Arch Intro & Basics:
    https://www.youtube.com/watch?v=zLP_X4wyHbY&list=PL5PHm2jkkXmi5CxxI7b3JCL1TWybTDtKq&index=1
 * - Parity & Hamming Code:
    Parity:
        https://www.youtube.com/watch?v=DdMcAUlxh1M
    Hamming Code:
        https://www.youtube.com/watch?v=1A_NcXxdoCc
        https://www.youtube.com/watch?v=JAMLuxdHH8o
    Error Checking:
        https://www.youtube.com/watch?v=wbH2VxzmoZk
 * - C
    * - K&R C book (ANSI C)
 - C++
    * - basics
    * - pointers
    * - functions
    * - references
    * - templates
    * - compilation
    * - scope & linkage
    * - namespaces
    * - OOP
    * - STL
    * - functors: http://www.cprogramming.com/tutorial/functors-function-objects-in-c++.html
    * - C++ at Google: https://www.youtube.com/watch?v=NOCElcMcFik
    * - Google C++ Style Guide: https://google.github.io/styleguide/cppguide.html
        - Google uses clang-format (Google setting)
    - C++ Core Guidelines: http://isocpp.github.io/CppCoreGuidelines/CppCoreGuidelines
    * - Efficiency with Algorithms, Performance with Data Structures: https://youtu.be/fHNmRkzxHWs
    - review: https://www.youtube.com/watch?v=Rub-JsjMhWY
 compilers:
    * - https://class.coursera.org/compilers-004/lecture/1
    * - https://class.coursera.org/compilers-004/lecture/2
    * - C++: https://www.youtube.com/watch?v=twodd1KFfGk
    * - Understanding Compiler Optimization (C++): https://www.youtube.com/watch?v=FnGCDLhaxKU
 how computers process a program:
    - https://www.youtube.com/watch?v=42KTvGYQYnA
    - https://www.youtube.com/watch?v=Mv2XQgpbTNE
    - https://www.youtube.com/watch?v=h8T3PWauYF4
 linked lists
    - https://www.coursera.org/learn/data-structures/lecture/OsBSF/arrays
    - singly-linked
        - https://www.coursera.org/learn/data-structures/lecture/kHhgK/singly-linked-lists
    - doubly-linked
        - https://www.coursera.org/learn/data-structures/lecture/jpGKD/doubly-linked-lists
    - reverse a singly-linked list
 stacks
    - see: https://class.coursera.org/algs4partI-010/lecture
    - https://www.coursera.org/learn/data-structures/lecture/UdKzQ/stacks
 queues
    - see: https://class.coursera.org/algs4partI-010/lecture
    - https://www.coursera.org/learn/data-structures/lecture/EShpq/queues
 arrays
    - https://www.coursera.org/learn/data-structures/lecture/OsBSF/arrays
    - https://www.coursera.org/learn/data-structures/lecture/EwbnV/dynamic-arrays
 Vectors
    - Vector calculus ?
 heaps
    - https://www.coursera.org/learn/data-structures/lecture/GRV2q/binary-trees
    - min heap
    - max heap
 Priority Queue
    - https://www.coursera.org/learn/data-structures/lecture/2OpTs/introduction
    - see: https://class.coursera.org/algs4partI-010/lecture
    - https://class.coursera.org/algs4partI-010/lecture/39
    - https://en.wikipedia.org/wiki/Priority_queue
 Disjoint Sets:
    - https://www.coursera.org/learn/data-structures/lecture/JssSY/overview
    - https://www.coursera.org/learn/data-structures/lecture/Mxu0w/trees
 hashtables
    - https://www.youtube.com/watch?v=C4Kc8xzcA68
    - https://class.coursera.org/algs4partI-010/lecture/52
    - https://www.coursera.org/learn/data-structures/home/week/3
    - see: https://class.coursera.org/algs4partI-010/lecture
    - https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/m7UuP/core-hash-tables
    - test: implement with only arrays
 tries
    - https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/08Xyf/core-introduction-to-tries
 Circular buffer/FIFO:
    - https://en.wikipedia.org/wiki/Circular_buffer
 Bit operations
    - count on bits
        - https://youtu.be/Hzuzo9NJrlc
    - max run of off bits
    - bit shifting
 binary search
 Sorting
    - no bubble sort - it's terrible
    - at least one n*log(n) sorting algorithm, preferably two (say, quicksort and merge sort)
    - Which algorithms can be used on lists? Which on arrays? Which on both? Is Quicksort stable?
    - algos:
        - mergesort
        - quicksort
 Caches
    - LRU cache
 Trees
    - https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/ovovP/core-trees
    - see: https://class.coursera.org/algs4partI-010/lecture
    - basic tree construction
    - traversal
    - manipulation algorithms
    - binary search trees BSTs
        - https://www.coursera.org/learn/data-structures/lecture/E7cXP/introduction
        - applications:
            - https://class.coursera.org/algs4partI-010/lecture/57
    - n-ary trees
    - trie-trees
    - at least one type of balanced binary tree (and know how it's implemented):
        - red/black tree
            - https://class.coursera.org/algs4partI-010/lecture/50
        - splay trees
            - https://www.coursera.org/learn/data-structures/lecture/O9nZ6/splay-trees
        - AVL trees
            - https://www.coursera.org/learn/data-structures/lecture/Qq5E0/avl-trees
            - https://www.coursera.org/learn/data-structures/lecture/PKEBC/avl-tree-implementation
            - https://www.coursera.org/learn/data-structures/lecture/22BgE/split-and-merge
        - 2-3 Search Trees
            - https://class.coursera.org/algs4partI-010/lecture/49
        - B-Trees:
            - https://class.coursera.org/algs4partI-010/lecture/51
    - BFS (breadth-first search)
    - DFS (depth-first search)
    - know the difference between
        - inorder
        - postorder
        - preorder
 Graphs:
    There are three basic ways to represent a graph in memory:
        - objects and pointers
        - matrix
        - adjacency list
    - familiarize yourself with each representation and its pros & cons
    - now their computational complexity, their tradeoffs, and how to implement them in real code
    - If you get a chance, try to study up on fancier algorithms:
        - Dijkstra
        - A*
 Other data structures:
    - You should study up on as many other data structures and algorithms as possible
    - You should especially know about the most famous classes of NP-complete problems, such as traveling salesman and the knapsack problem, and be able to recognize them when an interviewer asks you them in disguise.
    - Find out what NP-complete means.
 Recursion
    -  when it is appropriate to use it
 Algorithmic complexity
 open-ended problems
    - manipulate strings
    - manipulate patterns
 design patterns:
    - strategy
    - singleton
    - adapter
    - prototype
    - decorator
 Combinatorics (n choose k)
 Probability
 Dynamic Programming
 Processes, Threads, Concurrency issues
    - difference: https://www.quora.com/What-is-the-difference-between-a-process-and-a-thread
    - threads: https://www.youtube.com/playlist?list=PL5jc9xFGsL8E12so1wlMS0r0hTQoJL74M
        - stopped here: https://www.youtube.com/watch?v=_N0B5ua7oN8&list=PL5jc9xFGsL8E12so1wlMS0r0hTQoJL74M&index=4
    - locks
    - mutexes
    - semaphores
    - monitors
    - how they work
    - deadlock
    - livelock
 Process resource needs
 Thread resource needs
 Modern concurrency constructs with multicore processors
 Context switching
    - How context switching is initiated by the operating system and underlying hardware
 Scheduling
 Weighted random sampling
 Implement system routines
 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
 Testing
 Information theory:
    - Markov processes:
        - https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/waxgx/core-markov-text-generation
        - https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/gZhiC/core-implementing-markov-text-generation
    - https://www.khanacademy.org/computing/computer-science/informationtheory/moderninfotheory/v/symbol-rate-information-theory
    - includes Markov chain
 Bloom Filter
    - https://www.youtube.com/watch?v=-SuTGoFYjZs
    - http://blog.michaelschmatz.com/2016/04/11/how-to-write-a-bloom-filter-cpp/
 C (for basis of C)
 C++ (for interview answers)
 Machine Learning:
    - http://www.analyticsvidhya.com/blog/2016/04/neural-networks-python-theano/
    - review videos
    - intro in Goodreader on iPad
    - http://www.dataschool.io/
 ---
 When you have time:
 C++ Talks at CPPCon:
    - https://www.youtube.com/watch?v=hEx5DNLWGgA&index=2&list=PLHTh1InhhwT75gykhs7pqcR_uSiG601oh
 Compilers:
    - https://class.coursera.org/compilers-004/lecture
 Computer and processor architecture:
    - https://class.coursera.org/comparch-003/lecture
 Long series of C++ videos:
    - https://www.youtube.com/playlist?list=PLfVsf4Bjg79Cu5MYkyJ-u4SyQmMhFeC1C
 ---
 Biggest challenges faced
 Best/worst designs seen
 Ideas for improving existing products
    - my search idea (optimal result exhaustion and refresh)
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 ##  Videos:
 ##########################################################################################
 6.042: Math for CS (25 videos):
    - https://www.youtube.com/watch?v=L3LMbpZIKhQ&list=PLB7540DEDD482705B
 6.006: Intro to Algorithms (47 videos):
    - https://www.youtube.com/watch?v=HtSuA80QTyo&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&nohtml5=False
 6.033: Computer System Engineering (22 videos):
    - https://www.youtube.com/watch?v=zm2VP0kHl1M&list=PL6535748F59DCA484
 6.046: Design and Analysis of Algorithms (34 videos):
    - https://www.youtube.com/watch?v=2P-yW7LQr08&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp
 6.851: Advanced Data Structures (22 videos):
    - https://www.youtube.com/watch?v=T0yzrZL1py0&list=PLUl4u3cNGP61hsJNdULdudlRL493b-XZf
 Stanford: Programming Paradigms (17 videos)
    - https://www.youtube.com/watch?v=jTSvthW34GU&list=PLC0B8B318B7394B6F&nohtml5=False
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 ##  Articles:
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 - https://www.topcoder.com/community/data-science/data-science-tutorials/the-importance-of-algorithms/
 - http://highscalability.com/blog/2016/4/4/how-to-remove-duplicates-in-a-large-dataset-reducing-memory.html
 - http://highscalability.com/blog/2016/3/23/what-does-etsys-architecture-look-like-today.html
 - http://highscalability.com/blog/2016/3/21/to-compress-or-not-to-compress-that-was-ubers-question.html
 - http://highscalability.com/blog/2016/3/3/asyncio-tarantool-queue-get-in-the-queue.html
 - http://highscalability.com/blog/2016/2/25/when-should-approximate-query-processing-be-used.html
 - http://highscalability.com/blog/2016/2/23/googles-transition-from-single-datacenter-to-failover-to-a-n.html
 - http://highscalability.com/blog/2016/2/15/egnyte-architecture-lessons-learned-in-building-and-scaling.html
 - http://highscalability.com/blog/2016/2/1/a-patreon-architecture-short.html
 - http://highscalability.com/blog/2016/1/27/tinder-how-does-one-of-the-largest-recommendation-engines-de.html
 - http://highscalability.com/blog/2016/1/25/design-of-a-modern-cache.html
 - http://highscalability.com/blog/2016/1/13/live-video-streaming-at-facebook-scale.html
 - http://highscalability.com/blog/2016/1/11/a-beginners-guide-to-scaling-to-11-million-users-on-amazons.html
 - http://highscalability.com/blog/2015/12/16/how-does-the-use-of-docker-effect-latency.html
 - http://highscalability.com/blog/2015/12/14/does-amp-counter-an-existential-threat-to-google.html
 - http://highscalability.com/blog/2015/11/9/a-360-degree-view-of-the-entire-netflix-stack.html
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 ##  Papers:
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 Computing Weak Consistency in Polynomial Time
    - http://delivery.acm.org/10.1145/2770000/2767407/p395-golab.pdf?ip=104.200.154.80&id=2767407&acc=OA&key=4D4702B0C3E38B35%2E4D4702B0C3E38B35%2E4D4702B0C3E38B35%2E5945DC2EABF3343C&CFID=769944592&CFTOKEN=71654301&__acm__=1460506755_42d28e3f230cc8e733e2e9ed1ebe3605
 How Developers Search for Code: A Case Study
    - http://static.googleusercontent.com/media/research.google.com/en//pubs/archive/43835.pdf
 Borg, Omega, and Kubernetes
    - http://static.googleusercontent.com/media/research.google.com/en//pubs/archive/44843.pdf
 Continuous Pipelines at Google
    - http://static.googleusercontent.com/media/research.google.com/en//pubs/archive/43790.pdf
 AddressSanitizer: A Fast Address Sanity Checker
    - http://static.googleusercontent.com/media/research.google.com/en//pubs/archive/37752.pdf
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 ##  Interview Prep:
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 Videos:
    - https://www.youtube.com/watch?v=oWbUtlUhwa8&feature=youtu.be
    - https://www.youtube.com/watch?v=qc1owf2-220&feature=youtu.be
 Articles:
    - http://dondodge.typepad.com/the_next_big_thing/2010/09/how-to-get-a-job-at-google-interview-questions-hiring-process.html
    - http://steve-yegge.blogspot.com/2008/03/get-that-job-at-google.html
    - http://sites.google.com/site/steveyegge2/five-essential-phone-screen-questions
    - http://www.google.com/about/careers/lifeatgoogle/hiringprocess/
 Additional:
    - https://courses.csail.mit.edu/iap/interview/materials.php
    - http://www.coderust.com/blog/2014/04/10/effective-whiteboarding-during-programming-interviews/
    - https://www.youtube.com/watch?v=rEJzOhC5ZtQ&feature=youtu.be
    - https://www.youtube.com/watch?v=aClxtDcdpsQ&feature=youtu.be
    - https://www.youtube.com/watch?v=2cf9xo1S134&feature=youtu.be
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 ##  Books:
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 %%%%% Mentioned in Coaching %%%%%%%%%%%%%%%
 The Algorithm Design Manual
    http://sist.sysu.edu.cn/~isslxm/DSA/textbook/Skiena.-.TheAlgorithmDesignManual.pdf
 Algorithms and Programming: Problems and Solutions:
    http://www.amazon.com/Algorithms-Programming-Solutions-Alexander-Shen/dp/0817638474
 Read first:
 Programming Interviews Exposed: Secrets to Landing Your Next Job, 2nd Edition:
    http://www.wiley.com/WileyCDA/WileyTitle/productCd-047012167X.html
 Read second:
 Cracking the Coding Interview, Fourth Edition:
    http://www.amazon.com/Cracking-Coding-Interview-Fourth-Edition/dp/145157827X
 %%%%% Additional %%%%%%%%%%%%%%%
 Programming Pearls:
    - http://www.wou.edu/~jcm/Spring-P-2015/Programming%20Pearls%20(2nd%20Ed)%20Bentley.pdf
 The Google Resume:
    - https://www.uop.edu.jo/download/research/members/495_1887_llll.pdf
 * - C Programming Language, Vol 2
 * - C++ Primer Plus
 Clean Code
 Code Complete
 Introduction to Algorithms
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 ##  Coding exercises/challenges:
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 Recommended: LeetCode: https://leetcode.com/
 HackerRank: https://www.hackerrank.com/
 Codility: https://codility.com/programmers/
 Proect Euler: https://projecteuler.net/index.php?section=problems
 InterviewCake: https://www.interviewcake.com/
 InterviewBit: https://www.interviewbit.com/invite/icjf
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 ##  Code:
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 https://github.com/lekkas/c-algorithms
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 ##  Done.                                                                               ##
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`@ -1,3 +1,3 @@`
	`# Project 9894`	`# Project 9894`

	`TBD`	`This is a setup for this project, which is stealthy right now. Will add more detail soon.`