Merge pull request #640 from Drakkkath/patch-1

Improving the consistency of capitalization and punctuation

README.md

@@ -255,7 +255,7 @@ Sometimes the classes are not in session so you have to wait a couple of months,
 - [ ] Cracking The Coding Interview Set 1:
     - [ ] [Gayle L McDowell - Cracking The Coding Interview (video)](https://www.youtube.com/watch?v=rEJzOhC5ZtQ)
     - [ ] [Cracking the Coding Interview with Author Gayle Laakmann McDowell (video)](https://www.youtube.com/watch?v=aClxtDcdpsQ)
-- [ ] Cracking the Facebook Coding Interview
+- [ ] Cracking the Facebook Coding Interview:
     - [ ] [The Approach](https://www.youtube.com/watch?v=wCl9kvQGHPI)
     - [ ] [Problem Walkthrough](https://www.youtube.com/watch?v=4UWDyJq8jZg)
 - [ ] Prep Course:
@@ -281,7 +281,7 @@ You could also use these, but read around first. There may be caveats:
 - JavaScript
 - Ruby
 
-Here is an article I wrote about choosing a language for the interview: [Pick One Language for the Coding Interview](https://startupnextdoor.com/important-pick-one-language-for-the-coding-interview/)
+Here is an article I wrote about choosing a language for the interview: [Pick One Language for the Coding Interview](https://startupnextdoor.com/important-pick-one-language-for-the-coding-interview/).
 
 You need to be very comfortable in the language and be knowledgeable.
 
@@ -334,8 +334,8 @@ I haven't read these two, but they are highly rated and written by Sedgewick. He
 - [ ] [Algorithms in C++, Parts 1-4: Fundamentals, Data Structure, Sorting, Searching](https://www.amazon.com/Algorithms-Parts-1-4-Fundamentals-Structure/dp/0201350882/)
 - [ ] [Algorithms in C++ Part 5: Graph Algorithms](https://www.amazon.com/Algorithms-Part-Graph-3rd-Pt-5/dp/0201361183/)
 - [ ] [Open Data Structures in C++](https://opendatastructures.org/ods-cpp.pdf)
-    - Rich and detailed collection of Data Structures and Algorithms.
-    - Great for first-timers.
+    - Rich and detailed collection of Data Structures and Algorithms
+    - Great for first-timers
 
 If you have a better recommendation for C++, please let me know. Looking for a comprehensive resource.
 
@@ -351,13 +351,13 @@ OR:
 - [ ] [Data Structures and Algorithms in Java](https://www.amazon.com/Data-Structures-Algorithms-Michael-Goodrich/dp/1118771338/)
     - by Goodrich, Tamassia, Goldwasser
     - used as optional text for CS intro course at UC Berkeley
-    - see my book report on the Python version below. This book covers the same topics.
+    - see my book report on the Python version below. This book covers the same topics
 
 ### Python
 
 - [ ] [Data Structures and Algorithms in Python](https://www.amazon.com/Structures-Algorithms-Python-Michael-Goodrich/dp/1118290275/)
     - by Goodrich, Tamassia, Goldwasser
-    - I loved this book. It covered everything and more.
+    - I loved this book. It covered everything and more
     - Pythonic code
     - my glowing book report: https://startupnextdoor.com/book-report-data-structures-and-algorithms-in-python/
 - [ ] [Open Data Structures in Python](https://opendatastructures.org/ods-python.pdf)
@@ -377,7 +377,7 @@ Please, read so you won't make my mistakes:
 
 [Retaining Computer Science Knowledge](https://startupnextdoor.com/retaining-computer-science-knowledge/).
 
-A course recommended to me (haven't taken it): [Learning how to Learn](https://www.coursera.org/learn/learning-how-to-learn)
+A course recommended to me (haven't taken it): [Learning how to Learn](https://www.coursera.org/learn/learning-how-to-learn).
 
 ### 2. Use Flashcards
 
@@ -401,16 +401,16 @@ your brain.
 An alternative to using my flashcard site is [Anki](http://ankisrs.net/), which has been recommended to me numerous times. It uses a repetition system to help you remember.
 It's user-friendly, available on all platforms and has a cloud sync system. It costs $25 on iOS but is free on other platforms.
 
-My flashcard database in Anki format: https://ankiweb.net/shared/info/25173560 (thanks [@xiewenya](https://github.com/xiewenya))
+My flashcard database in Anki format: https://ankiweb.net/shared/info/25173560 (thanks [@xiewenya](https://github.com/xiewenya)).
 
-### 3. Start doing coding interview questions while you're learning data structures and algorithms, 
+### 3. Start doing coding interview questions while you're learning data structures and algorithms 
 
 You need to apply what you're learning to solving problems, or you'll forget. I made this mistake. Once you've learned a topic, 
 and feel comfortable with it, like linked lists, open one of the coding interview books and do a couple of questions regarding 
 linked lists. Then move on to the next learning topic. Then later, go back and do another linked list problem, 
 or recursion problem, or whatever. But keep doing problems while you're learning. You're not being hired for knowledge, 
 but how you apply the knowledge. There are several books and sites I recommend. 
-See here for more: [Coding Question Practice](#coding-question-practice)
+See here for more: [Coding Question Practice](#coding-question-practice).
 
 ### 4. Review, review, review
 
@@ -436,12 +436,12 @@ These are prevalent technologies but not part of this study plan:
 Some subjects take one day, and some will take multiple days. Some are just learning with nothing to implement.
 
 Each day I take one subject from the list below, watch videos about that subject, and write an implementation in:
-- C - using structs and functions that take a struct * and something else as args.
+- C - using structs and functions that take a struct * and something else as args
 - C++ - without using built-in types
 - C++ - using built-in types, like STL's std::list for a linked list
 - Python - using built-in types (to keep practicing Python)
 - and write tests to ensure I'm doing it right, sometimes just using simple assert() statements
-- You may do Java or something else, this is just my thing.
+- You may do Java or something else, this is just my thing
 
 You don't need all these. You need only [one language for the interview](#pick-one-language-for-the-interview).
 
@@ -464,10 +464,10 @@ Write code on a whiteboard or paper, not a computer. Test with some sample input
 ## Prerequisite Knowledge
 
 - [ ] **Learn C**
-    - C is everywhere. You'll see examples in books, lectures, videos, *everywhere* while you're studying.
+    - C is everywhere. You'll see examples in books, lectures, videos, *everywhere* while you're studying
     - [ ] [The C Programming Language, Vol 2](https://www.amazon.com/Programming-Language-Brian-W-Kernighan/dp/0131103628)
         - This is a short book, but it will give you a great handle on the C language and if you practice it a little
-            you'll quickly get proficient. Understanding C helps you understand how programs and memory work.
+            you'll quickly get proficient. Understanding C helps you understand how programs and memory work
         - [Answers to questions](https://github.com/lekkas/c-algorithms)
 
 - [ ] **How computers process a program:**
@@ -480,8 +480,8 @@ Write code on a whiteboard or paper, not a computer. Test with some sample input
 ## Algorithmic complexity / Big-O / Asymptotic analysis
 
 - Nothing to implement
-- There are a lot of videos here. Just watch enough until you understand it. You can always come back and review.
-- If some lectures are too mathy, you can jump down to the bottom and watch the discrete mathematics videos to get the background knowledge.
+- There are a lot of videos here. Just watch enough until you understand it. You can always come back and review
+- If some lectures are too mathy, you can jump down to the bottom and watch the discrete mathematics videos to get the background knowledge
 - [ ] [Harvard CS50 - Asymptotic Notation (video)](https://www.youtube.com/watch?v=iOq5kSKqeR4)
 - [ ] [Big O Notations (general quick tutorial) (video)](https://www.youtube.com/watch?v=V6mKVRU1evU)
 - [ ] [Big O Notation (and Omega and Theta) - best mathematical explanation (video)](https://www.youtube.com/watch?v=ei-A_wy5Yxw&index=2&list=PL1BaGV1cIH4UhkL8a9bJGG356covJ76qN)
@@ -545,7 +545,7 @@ Write code on a whiteboard or paper, not a computer. Test with some sample input
         - [ ] [CS 61B - Linked Lists 1 (video)](https://archive.org/details/ucberkeley_webcast_htzJdKoEmO0)
         - [ ] [CS 61B - Linked Lists 2 (video)](https://archive.org/details/ucberkeley_webcast_-c4I3gFYe3w)
     - [ ] [C Code (video)](https://www.youtube.com/watch?v=QN6FPiD0Gzo)
-            - not the whole video, just portions about Node struct and memory allocation.
+            - not the whole video, just portions about Node struct and memory allocation
     - [ ] Linked List vs Arrays:
         - [Core Linked Lists Vs Arrays (video)](https://www.coursera.org/lecture/data-structures-optimizing-performance/core-linked-lists-vs-arrays-rjBs9)
         - [In The Real World Linked Lists Vs Arrays (video)](https://www.coursera.org/lecture/data-structures-optimizing-performance/in-the-real-world-lists-vs-arrays-QUaUd)
@@ -576,7 +576,7 @@ Write code on a whiteboard or paper, not a computer. Test with some sample input
 - ### Stack
     - [ ] [Stacks (video)](https://www.coursera.org/lecture/data-structures/stacks-UdKzQ)
     - [ ] [Using Stacks Last-In First-Out (video)](https://archive.org/details/0102WhatYouShouldKnow/05_01-usingStacksForLast-inFirst-out.mp4)
-    - [ ] Will not implement. Implementing with array is trivial.
+    - [ ] Will not implement. Implementing with array is trivial
 
 - ### Queue
     - [ ] [Using Queues First-In First-Out(video)](https://archive.org/details/0102WhatYouShouldKnow/05_03-usingQueuesForFirst-inFirst-out.mp4)
@@ -757,7 +757,7 @@ Write code on a whiteboard or paper, not a computer. Test with some sample input
         - I wouldn't recommend sorting a linked list, but merge sort is doable.
         - [Merge Sort For Linked List](http://www.geeksforgeeks.org/merge-sort-for-linked-list/)
 
-- For heapsort, see Heap data structure above. Heap sort is great, but not stable.
+- For heapsort, see Heap data structure above. Heap sort is great, but not stable
 
 - [ ] [Sedgewick - Mergesort (5 videos)](https://www.coursera.org/learn/algorithms-part1/home/week/3)
     - [ ] [1. Mergesort](https://www.coursera.org/learn/algorithms-part1/lecture/ARWDq/mergesort)
@@ -799,7 +799,7 @@ Write code on a whiteboard or paper, not a computer. Test with some sample input
     - [ ] Mergesort: O(n log n) average and worst case
     - [ ] Quicksort O(n log n) average case
     - Selection sort and insertion sort are both O(n^2) average and worst case
-    - For heapsort, see Heap data structure above.
+    - For heapsort, see Heap data structure above
 
 - [ ] Not required, but I recommended them:
     - [ ] [Sedgewick - Radix Sorts (6 videos)](https://www.coursera.org/learn/algorithms-part2/home/week/3)
@@ -830,7 +830,7 @@ Graphs can be used to represent many problems in computer science, so this secti
         - adjacency map
     - Familiarize yourself with each representation and its pros & cons
     - BFS and DFS - know their computational complexity, their trade offs, and how to implement them in real code
-    - When asked a question, look for a graph-based solution first, then move on if none.
+    - When asked a question, look for a graph-based solution first, then move on if none
 
 - [ ] MIT(videos):
     - [ ] [Breadth-First Search](https://www.youtube.com/watch?v=s-CYnVz-uh4&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=13)
@@ -886,8 +886,8 @@ Graphs can be used to represent many problems in computer science, so this secti
         - [ ] [Lecture 9 | Programming Abstractions (video)](https://www.youtube.com/watch?v=uFJhEPrbycQ&list=PLFE6E58F856038C69&index=9)
         - [ ] [Lecture 10 | Programming Abstractions (video)](https://www.youtube.com/watch?v=NdF1QDTRkck&index=10&list=PLFE6E58F856038C69)
         - [ ] [Lecture 11 | Programming Abstractions (video)](https://www.youtube.com/watch?v=p-gpaIGRCQI&list=PLFE6E58F856038C69&index=11)
-    - when it is appropriate to use it
-    - how is tail recursion better than not?
+    - When it is appropriate to use it?
+    - How is tail recursion better than not?
         - [ ] [What Is Tail Recursion Why Is It So Bad?](https://www.quora.com/What-is-tail-recursion-Why-is-it-so-bad)
         - [ ] [Tail Recursion (video)](https://www.youtube.com/watch?v=L1jjXGfxozc)
 
@@ -998,16 +998,16 @@ Graphs can be used to represent many problems in computer science, so this secti
     - [What Is The Difference Between A Process And A Thread?](https://www.quora.com/What-is-the-difference-between-a-process-and-a-thread)
     - Covers:
         - Processes, Threads, Concurrency issues
-            - difference between processes and threads
-            - processes
-            - threads
-            - locks
-            - mutexes
-            - semaphores
-            - monitors
-            - how they work
-            - deadlock
-            - livelock
+            - Difference between processes and threads
+            - Processes
+            - Threads
+            - Locks
+            - Mutexes
+            - Semaphores
+            - Monitors
+            - How they work?
+            - Deadlock
+            - Livelock
         - CPU activity, interrupts, context switching
         - Modern concurrency constructs with multicore processors
         - [Paging, segmentation and virtual memory (video)](https://www.youtube.com/watch?v=LKe7xK0bF7o&list=PLCiOXwirraUCBE9i_ukL8_Kfg6XNv7Se8&index=2)
@@ -1016,7 +1016,7 @@ Graphs can be used to represent many problems in computer science, so this secti
         - Thread resource needs (shares above (minus stack) with other threads in the same process but each has its own pc, stack counter, registers, and stack)
         - Forking is really copy on write (read-only) until the new process writes to memory, then it does a full copy.
         - Context switching
-            - How context switching is initiated by the operating system and underlying hardware
+            - How context switching is initiated by the operating system and underlying hardware?
     - [ ] [threads in C++ (series - 10 videos)](https://www.youtube.com/playlist?list=PL5jc9xFGsL8E12so1wlMS0r0hTQoJL74M)
     - [ ] concurrency in Python (videos):
         - [ ] [Short series on threads](https://www.youtube.com/playlist?list=PL1H1sBF1VAKVMONJWJkmUh6_p8g4F2oy1)
@@ -1043,8 +1043,8 @@ Graphs can be used to represent many problems in computer science, so this secti
     - [ ] [How to write tests](http://jasonpolites.github.io/tao-of-testing/ch4-1.1.html)
 
 - ### Scheduling
-    - in an OS, how it works
-    - can be gleaned from Operating System videos
+    - In an OS, how it works?
+    - Can be gleaned from Operating System videos
 
 - ### String searching & manipulations
     - [ ] [Sedgewick - Suffix Arrays (video)](https://www.coursera.org/learn/algorithms-part2/lecture/TH18W/suffix-arrays)
@@ -1056,12 +1056,12 @@ Graphs can be used to represent many problems in computer science, so this secti
         - [ ] [5. Rabin-Karp](https://www.coursera.org/learn/algorithms-part2/lecture/3KiqT/rabin-karp)
     - [ ] [Search pattern in text (video)](https://www.coursera.org/learn/data-structures/lecture/tAfHI/search-pattern-in-text)
 
-    If you need more detail on this subject, see "String Matching" section in [Additional Detail on Some Subjects](#additional-detail-on-some-subjects)
+    If you need more detail on this subject, see "String Matching" section in [Additional Detail on Some Subjects](#additional-detail-on-some-subjects).
 
 - ### Tries
     - Note there are different kinds of tries. Some have prefixes, some don't, and some use string instead of bits
-        to track the path.
-    - I read through code, but will not implement.
+        to track the path
+    - I read through code, but will not implement
     - [ ] [Sedgewick - Tries (3 videos)](https://www.coursera.org/learn/algorithms-part2/home/week/4)
         - [ ] [1. R Way Tries](https://www.coursera.org/learn/algorithms-part2/lecture/CPVdr/r-way-tries)
         - [ ] [2. Ternary Search Tries](https://www.coursera.org/learn/algorithms-part2/lecture/yQM8K/ternary-search-tries)
@@ -1093,7 +1093,7 @@ Graphs can be used to represent many problems in computer science, so this secti
 
 - ### Networking
     - **if you have networking experience or want to be a reliability engineer or operations engineer, expect questions**
-    - otherwise, this is just good to know
+    - Otherwise, this is just good to know
     - [ ] [Khan Academy](https://www.khanacademy.org/computing/computer-science/computers-and-internet-code-org)
     - [ ] [UDP and TCP: Comparison of Transport Protocols (video)](https://www.youtube.com/watch?v=Vdc8TCESIg8)
     - [ ] [TCP/IP and the OSI Model Explained! (video)](https://www.youtube.com/watch?v=e5DEVa9eSN0)
@@ -1114,13 +1114,13 @@ Graphs can be used to represent many problems in computer science, so this secti
 
 - 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.
+      Expect to spend quite a bit of time on this
 - Considerations:
-    - scalability
+    - Scalability
         - Distill large data sets to single values
         - Transform one data set to another
         - Handling obscenely large amounts of data
-    - system design
+    - System design
         - features sets
         - interfaces
         - class hierarchies
@@ -1134,7 +1134,7 @@ Graphs can be used to represent many problems in computer science, so this secti
 - [ ] [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/)
 - [ ] [Algorithm design](http://www.hiredintech.com/algorithm-design/)
 - [ ] [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.
+- [ ] [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)
@@ -1201,30 +1201,30 @@ Graphs can be used to represent many problems in computer science, so this secti
     - [ ] 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.
+    - 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/master/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
+            - 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
+            - 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
+            - 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 CDN network: old article](https://kilthub.cmu.edu/articles/Globally_distributed_content_delivery/6605972)
         - [Design a random unique ID generation system](https://blog.twitter.com/2010/announcing-snowflake)
@@ -1258,12 +1258,12 @@ Now that you know all the computer science topics above, it's time to practice a
 **Coding question practice is not about memorizing answers to programming problems.**
 
 Why you need to practice doing programming problems:
-- problem recognition, and where the right data structures and algorithms fit in
-- gathering requirements for the problem
-- talking your way through the problem like you will in the interview
-- coding on a whiteboard or paper, not a computer
-- coming up with time and space complexity for your solutions
-- testing your solutions
+- Problem recognition, and where the right data structures and algorithms fit in
+- Gathering requirements for the problem
+- Talking your way through the problem like you will in the interview
+- Coding on a whiteboard or paper, not a computer
+- Coming up with time and space complexity for your solutions
+- Testing your solutions
 
 There is a great intro for methodical, communicative problem solving in an interview. You'll get this from the programming
 interview books, too, but I found this outstanding:
@@ -1304,15 +1304,15 @@ Take coding challenges every day, as many as you can.
 Coding Interview Question Videos:
 - [IDeserve (88 videos)](https://www.youtube.com/watch?v=NBcqBddFbZw&list=PLamzFoFxwoNjPfxzaWqs7cZGsPYy0x_gI)
 - [Tushar Roy (5 playlists)](https://www.youtube.com/user/tusharroy2525/playlists?shelf_id=2&view=50&sort=dd)
-    - Super for walkthroughs of problem solutions.
+    - Super for walkthroughs of problem solutions
 - [Nick White - LeetCode Solutions (187 Videos)](https://www.youtube.com/playlist?list=PLU_sdQYzUj2keVENTP0a5rdykRSgg9Wp-)
-    - Good explanations of solution and the code.
-    - You can watch several in a short time.
+    - Good explanations of solution and the code
+    - You can watch several in a short time
 - [FisherCoder - LeetCode Solutions](https://youtube.com/FisherCoder)
 
 Challenge sites:
 - [LeetCode](https://leetcode.com/)
-    - My favorite coding problem site. It's worth the subscription money for the 1-2 months you'll likely be preparing.
+    - My favorite coding problem site. It's worth the subscription money for the 1-2 months you'll likely be preparing
     - [LeetCode solutions from FisherCoder](https://github.com/fishercoder1534/Leetcode) 
     - See Nick White Videos above for short code-throughs
 - [HackerRank](https://www.hackerrank.com/)
@@ -1334,9 +1334,9 @@ Challenge repos:
 - [Interactive Coding Interview Challenges in Python](https://github.com/donnemartin/interactive-coding-challenges)
 
 Mock Interviews:
-- [Gainlo.co: Mock interviewers from big companies](http://www.gainlo.co/) - I used this and it helped me relax for the phone screen and on-site interview.
+- [Gainlo.co: Mock interviewers from big companies](http://www.gainlo.co/) - I used this and it helped me relax for the phone screen and on-site interview
 - [Pramp: Mock interviews from/with peers](https://www.pramp.com/) - peer-to-peer model of practice interviews
-- [Refdash: Mock interviews and expedited interviews](https://refdash.com/) - also help candidates fast track by skipping multiple interviews with tech companies.
+- [Refdash: Mock interviews and expedited interviews](https://refdash.com/) - also help candidates fast track by skipping multiple interviews with tech companies
 - [interviewing.io: Practice mock interview with senior engineers](https://interviewing.io) - anonymous algorithmic/systems design interviews with senior engineers from FAANG anonymously. 
 
 
@@ -1360,7 +1360,7 @@ Have a story, not just data, about something you accomplished.
 - What's a tough problem you've solved?
 - Biggest challenges faced?
 - Best/worst designs seen?
-- Ideas for improving an existing product.
+- Ideas for improving an existing product
 - How do you work best, as an individual and as part of a team?
 - Which of your skills or experiences would be assets in the role and why?
 - What did you most enjoy at [job x / project y]?
@@ -1411,40 +1411,40 @@ You're never really done.
     These are here so you can dive into a topic you find interesting.
 
 - [The Unix Programming Environment](https://www.amazon.com/dp/013937681X)
-    - an oldie but a goodie
+    - An oldie but a goodie
 - [The Linux Command Line: A Complete Introduction](https://www.amazon.com/dp/1593273894/)
-    - a modern option
+    - 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
+    - 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
+    - AKA the "Gang Of Four" book, or GOF
+    - The canonical design patterns book
 - [UNIX and Linux System Administration Handbook, 5th Edition](https://www.amazon.com/UNIX-Linux-System-Administration-Handbook/dp/0134277554/)
 - [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.
+    - 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.
-            - about to get to this part. Will update here once I've made my way through it.
+        - 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
+            - About to get to this part. Will update here once I've made my way through it
     - 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.
+    - 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
@@ -1456,15 +1456,15 @@ You're never really done.
         - 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
+    - **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
 
 - [Programming Pearls](http://www.amazon.com/Programming-Pearls-2nd-Jon-Bentley/dp/0201657880)
     - The first couple of chapters present clever solutions to programming problems (some very old using data tape) but
-      that is just an intro. This a guidebook on program design and architecture.
+      that is just an intro. This a guidebook on program design and architecture
 
 ## Additional Learning
     
@@ -1518,7 +1518,7 @@ You're never really done.
         - [Core Markov Text Generation](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/waxgx/core-markov-text-generation)
         - [Core Implementing Markov Text Generation](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/gZhiC/core-implementing-markov-text-generation)
         - [Project = Markov Text Generation Walk Through](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/EUjrq/project-markov-text-generation-walk-through)
-    - See more in MIT 6.050J Information and Entropy series below.
+    - See more in MIT 6.050J Information and Entropy series below
 
 - ### Parity & Hamming Code (videos)
     - [Intro](https://www.youtube.com/watch?v=q-3BctoUpHE)
@@ -1529,19 +1529,19 @@ You're never really done.
     - [Error Checking](https://www.youtube.com/watch?v=wbH2VxzmoZk)
 
 - ### Entropy
-    - also see videos below
-    - make sure to watch information theory videos first
+    - Also see videos below
+    - Make sure to watch information theory videos first
     - [Information Theory, Claude Shannon, Entropy, Redundancy, Data Compression & Bits (video)](https://youtu.be/JnJq3Py0dyM?t=176)
 
 - ### Cryptography
-    - also see videos below
-    - make sure to watch information theory videos first
+    - Also see videos below
+    - Make sure to watch information theory videos first
     - [Khan Academy Series](https://www.khanacademy.org/computing/computer-science/cryptography)
     - [Cryptography: Hash Functions](https://www.youtube.com/watch?v=KqqOXndnvic&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=30)
     - [Cryptography: Encryption](https://www.youtube.com/watch?v=9TNI2wHmaeI&index=31&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp)
 
 - ### Compression
-    - make sure to watch information theory videos first
+    - Make sure to watch information theory videos first
     - Computerphile (videos):
         - [Compression](https://www.youtube.com/watch?v=Lto-ajuqW3w)
         - [Entropy in Compression](https://www.youtube.com/watch?v=M5c_RFKVkko)
@@ -1621,8 +1621,8 @@ You're never really done.
     - [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.
+    - 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
@@ -1639,11 +1639,11 @@ You're never really done.
         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
+        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.
+        - 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**
@@ -1652,7 +1652,7 @@ You're never really done.
             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).
+            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)
@@ -1662,7 +1662,7 @@ You're never really done.
         - 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.
+            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.
@@ -1677,7 +1677,7 @@ You're never really done.
             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.
+            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)
@@ -1713,7 +1713,7 @@ You're never really done.
             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.
+            (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)
@@ -1725,8 +1725,8 @@ You're never really done.
 
 
 - ### k-D Trees
-    - great for finding number of points in a rectangle or higher dimension object
-    - a good fit for k-nearest neighbors
+    - 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)