another fix to formatting

MachineLearning.md

@@ -67,7 +67,7 @@ List of topics focusing on theoretical components:
 
 * Nonparametric Methods
 * Decision Trees
-* Lienar iscrimination
+* Linear discrimination
 * Miultilyaer Perceptrons
 * Local Models
 * Kernel Machines
@@ -76,7 +76,6 @@ List of topics focusing on theoretical components:
 * Graphical Models
 * Combining Multiple Learners
 * Reinforcement Learning
-
 * Design and Analysis of Machine Learning Experiments
 
 
@@ -84,8 +83,7 @@ List of topics focusing on theoretical components:
 
 A long and full list of types of models under each sub-heading: 
 
-* Regression
-	* **Modeling relationship between variables, iteratively refined using an error measure.**
+* Regression: **Modeling relationship between variables, iteratively refined using an error measure.**
 	* Linear Regression
 	* Logistic Regression
 	* OLS (Ordinary Least Squares) Regression
@@ -93,55 +91,47 @@ A long and full list of types of models under each sub-heading:
 	* MARS (Multivariate Adaptive Regression Splines)
 	* LOESS (Locally Estimated Scatterplot Smoothing)
 
-* Instance Based
-	* **Build up database of data, compare new data to database; winner-take-all or memory-based learning.**
+* Instance Based: **Build up database of data, compare new data to database; winner-take-all or memory-based learning.**
 	* k-Nearest Neighbor
 	* Learning Vector quantization
 	* Self-Organizing Map
 	* Localy Weighted Learning
 
-* Regularization
-	* **Extension made to other methods, penalizes model complexity, favors simpler and more generalizable models.**
+* Regularization: **Extension made to other methods, penalizes model complexity, favors simpler and more generalizable models.**
 	* Ridge Regression
 	* LASSO (Least Absolute Shrinkage and Selection Operator)
 	* Elastic Net
 	* LARS (Least Angle Regression)
 
-* Decision Tree
-	* **Construct a model of decisions made on actual values of attributes in the data.**
+* Decision Tree: **Construct a model of decisions made on actual values of attributes in the data.**
 	* Classification and Regression Tree
 	* CHAID (Chi-Squared Automatic Interaction Detection)
 	* Conditional Decision Trees
 
-* Bayesian
-	* **Methods explicitly applying Bayes' Theorem for classification and regression problems.**
+* Bayesian: **Methods explicitly applying Bayes' Theorem for classification and regression problems.**
 	* Naive Bayes
 	* Gaussian Naive Bayes
 	* Multinomial Naive Bayes
 	* Bayesian Network
 	* BBN (Bayesian Belief Network)
 
-* Clustering
-	* **Centroid-based and hierarchical modeling approaches; groups of maximum commonality.**
+* Clustering: **Centroid-based and hierarchical modeling approaches; groups of maximum commonality.**
 	* k-Means
 	* k-Medians
 	* Expectation Maximization
 	* Hierarchical Clustering
 
-* Association Rule Algorithms 
-	* **Extract rules that best explain relationships between variables in data.**
+* Association Rule Algorithms: **Extract rules that best explain relationships between variables in data.**
 	* Apriori algorithm
 	* Eclat algorithm
 
-* Neural Networks
-	* **Inspired by structure and function of biological neural networks, used ofr regression and classification problems.**
+* Neural Networks: **Inspired by structure and function of biological neural networks, used ofr regression and classification problems.**
 	* Radial Basis Function Network (RBFN)
 	* Perceptron
 	* Back-Propagation
 	* Hopfield Network
 
-* Deep Learning
-	* **Neural networks that exploit cheap and abundant computational power; semi-supervised, lots of data.**
+* Deep Learning: **Neural networks that exploit cheap and abundant computational power; semi-supervised, lots of data.**
 	* Convolutional Neural Network (CNN)
 	* Recurrent Neural Network (RNN)
 	* Long-Short-Term Memory Network (LSTM)
@@ -149,8 +139,7 @@ A long and full list of types of models under each sub-heading:
 	* Deep Belief Network (DBN)
 	* Stacked Auto-Encoders
 
-* Dimensionality Reduction
-	* **Find inherent structure in data, in an unsupervised manner, to describe data using less information.**
+* Dimensionality Reduction: **Find inherent structure in data, in an unsupervised manner, to describe data using less information.**
 	* PCA
 	* t-SNE
 	* PLS (Partial Least Squares Regression)
@@ -164,8 +153,7 @@ A long and full list of types of models under each sub-heading:
 	* Regularized Discriminant Analysis
 	* Linear Discriminant Analysis
 
-* Ensemble
-	* **Models composed of multiple weaker models, independently trained, that provide a combined prediction.**
+* Ensemble: **Models composed of multiple weaker models, independently trained, that provide a combined prediction.**
 	* Random Forest
 	* Gradient Boosting Machines (GBM)
 	* Boosting
@@ -174,4 +162,3 @@ A long and full list of types of models under each sub-heading:
 	* Stacked Generalization (Blending)
 	* Gradient Boosted Regression Trees
 
-

README.md

@@ -15,22 +15,13 @@ See [ThePlan.md](/ThePlan.md)
 
 ### Software Engineering
 
-The basic concepts, the full topic list, the to do list.
+Full list of software engineering topics: [SoftwareEngineering.md](/SoftwareEngineering.md)
 
-See [SoftwareEngineering.md](/SoftwareEngineering.md)
-
-### TODO Software Engineering
-
-See [TODOSoftwareEngineering.md](/TODOSoftwareEngineering.md)
+Schedule and task list (ended August 2017): [TODOSoftwareEngineering.md](/TODOSoftwareEngineering.md)
 
 --------
 
 ### Machine Learning
 
-The basic concepts and the detailed topic list.
+Full list of machine learning topics: [MachineLearning.md](/MachineLearning.md)
 
-See [MachineLearning.md](/MachineLearning.md)
-
-### TODO Machine Learning
-
-See [TODOMachineLearning.md](/TODOMachineLearning.md)

TODONumerics.md

@@ -9,9 +9,11 @@
 	* Parabolas
 	* Points, spaces, curves, 2D vs 3D
 
+
 * Solutions of linear algebraic equations
 	* Linear system, matrix solvers
 
+
 * Interpolation and extrapolation
 
 * Integration
@@ -36,28 +38,21 @@
 * Chapter 2 - solutions of linear algebraic equations
 * Chapter 3 - interpolation and extrapolation
 * Chapter 4 - Integration of Functions
-
 * Chapter 5 - Evaluation of Functions
 * Chapter 6 - Special Functions
-
-Chapter 7 - Random numbers
-Chapter 8 - Sorting and selection
-Chapter 9 - Root finding and nonlinear equations
-Chapter 10 - Minimization and maximization
-
-Chapter 11 - Eigensystems
-Chapter 12 - Fast Fourier Transform
-Chapter 13 - Fourier and spectral applications
-Chapter 14 - Statistical description of data
-
-Chapter 15 - Modeling of data
-Chapter 16 - Classification and Inference
-Chapter 17 - Integration of ODEs
-
-Chapter 18 - Two-point boundary solution
-Chapter 19 - Integral equations and inverse theory
-
-Chapter 20 - PDEs
-
-Chapter 21 - Computational geometry
+* Chapter 7 - Random numbers
+* Chapter 8 - Sorting and selection
+* Chapter 9 - Root finding and nonlinear equations
+* Chapter 10 - Minimization and maximization
+* Chapter 11 - Eigensystems
+* Chapter 12 - Fast Fourier Transform
+* Chapter 13 - Fourier and spectral applications
+* Chapter 14 - Statistical description of data
+* Chapter 15 - Modeling of data
+* Chapter 16 - Classification and Inference
+* Chapter 17 - Integration of ODEs
+* Chapter 18 - Two-point boundary solution
+* Chapter 19 - Integral equations and inverse theory
+* Chapter 20 - PDEs
+* Chapter 21 - Computational geometry
 

TODOSoftwareEngineering.md

@@ -1,7 +1,7 @@
 # TODO List - Software Engineering 
 
 Table of Contents:
-* [Data Structures](#Data Structures)
+* [Data Structures](#data-structures)
 	* [Arrays](#arrays)
 	* [Linked Lists](#ll)
 	* [Stacks and Queues](#sq)
@@ -10,13 +10,9 @@ Table of Contents:
 	* [Dictionaries and Maps and Hash Tables](#dict)
 	* [Sets, Skip Lists](#sets)
 	* [Search Trees](#searchtrees)
-	* [Advanced Data Structures (Skiena)](#adv)
 	* [Graphs](#graphs)
+	* [Advanced Data Structures (Skiena)](#adv)
 	* [Study Guides](#studyguides)
-* [Data Structures and Libraries](#lib)
-	* Guava
-	* Apache Commons
-	* Others
 * [Algorithms](#algorithms)
 	* [Complexity and Big O Notation](#bigO)
 	* [Timing](#timing)
@@ -29,16 +25,17 @@ Table of Contents:
 * [OOP](#oop)
 * [Java](#java)
 * [Practice and Applications](#practice)
-	* [Blogging and Wrtiting](#blogging)
+	* [Blogging and Writing](#blogging)
 	* [Project Euler](#euler)
 	* [ICPC](#icpc)
 	* [Google Code Jam](#codejam)
+* [Engineering Interview Notes](#interview-notes)
 
 
 
 
 
-<a name="data_structures"></a>
+<a name="data-structures"></a>
 ## Data Structures
 
 <a name="arrays"></a>
@@ -82,7 +79,6 @@ Table of Contents:
 	- Fisher Yates [https://charlesreid1.com/wiki/Arrays/Java/FisherYates](https://charlesreid1.com/wiki/Arrays/Java/FisherYates)
 	- Python list [https://charlesreid1.com/wiki/Arrays/Java/PythonList](https://charlesreid1.com/wiki/Arrays/Java/PythonList)
 	- Removing elements 
-
 - Code:
 	- Python-style list in Java: [https://charlesreid1.com:3000/cs/java/src/master/arrays/python-list/PythonList.java](https://charlesreid1.com:3000/cs/java/src/master/arrays/python-list/PythonList.java)
 	- Usage of the Array data type: [https://charlesreid1.com:3000/cs/java/src/master/arrays](https://charlesreid1.com:3000/cs/java/src/master/arrays)
@@ -112,7 +108,7 @@ Table of Contents:
 
 ---
 
-[ ] Linked lists: Python
+[X] Linked lists: Python
  - Singly liked lists: 06/04
  - Books:
 	- Goodrich Python Chapter 7
@@ -121,7 +117,6 @@ Table of Contents:
 	- [https://charlesreid1.com/wiki/Linked_Lists](https://charlesreid1.com/wiki/Linked_Lists)
 	- [https://charlesreid1.com/wiki/Linked_Lists/Python](https://charlesreid1.com/wiki/Linked_Lists/Python)
 	- [https://charlesreid1.com/wiki/Linked_Lists/Python/Single](https://charlesreid1.com/wiki/Linked_Lists/Python/Single)
-- End of chapter questions:
 - Code:
 
 
@@ -139,8 +134,6 @@ Table of Contents:
 - Wiki notes:
 	- [https://charlesreid1.com/wiki/StacksQueues](https://charlesreid1.com/wiki/StacksQueues)
 	- [https://charlesreid1.com/wiki/StacksQueues/Python](https://charlesreid1.com/wiki/StacksQueues/Python)
-- End of chapter questions: 
-	- (none) 
 - Code:
 	- Python: [https://charlesreid1.com:3000/cs/python/src/master/stacks-queues-deques/](https://charlesreid1.com:3000/cs/python/src/master/stacks-queues-deques/)
 	- Array-based stack: [https://charlesreid1.com:3000/cs/python/src/master/stacks-queues-deques/stacks/ArrayStack.py](https://charlesreid1.com:3000/cs/python/src/master/stacks-queues-deques/stacks/ArrayStack.py)
@@ -165,9 +158,6 @@ Table of Contents:
 	- [https://charlesreid1.com/wiki/StacksQueues/Java/LinkedStack](https://charlesreid1.com/wiki/StacksQueues/Java/LinkedStack)
 	- [https://charlesreid1.com/wiki/StacksQueues/Java/LinkedQueue](https://charlesreid1.com/wiki/StacksQueues/Java/LinkedQueue)
 	- [https://charlesreid1.com/wiki/StacksQueues/Java/LinkedDeque](https://charlesreid1.com/wiki/StacksQueues/Java/LinkedDeque)
-- End of chapter questions:
-	- Goodrich
-	- To do
 - Implementations/Code:
 	- Array based stack: [https://charlesreid1.com:3000/cs/java/src/master/stacks-queues-deques/stacks/ArrayStack.java](https://charlesreid1.com:3000/cs/java/src/master/stacks-queues-deques/stacks/ArrayStack.java)
 	- Array based queue: [https://charlesreid1.com:3000/cs/java/src/master/stacks-queues-deques/queues/ArrayQueue.java](https://charlesreid1.com:3000/cs/java/src/master/stacks-queues-deques/queues/ArrayQueue.java)
@@ -197,13 +187,12 @@ Table of Contents:
 	- Goodrich trees coverage includes patterns, abstract methods
 - Wiki notes:
 	- [https://charlesreid1.com/wiki/Template:TreesFlag](https://charlesreid1.com/wiki/Template:TreesFlag)
-- End of chapter questions:
 
 
 ---
 
 
-[ ] Trees: Java
+[X] Trees: Java
 - 06/10 - 06/13, 06/15 - 06/16
 - Books:
 	- Goodrich Java Chapter 8
@@ -219,13 +208,14 @@ Table of Contents:
 	- Skiena: [https://charlesreid1.com/wiki/Tree/LogN_Min_Search](https://charlesreid1.com/wiki/Tree/LogN_Min_Search)
 	- Expression trees: [https://charlesreid1.com/wiki/Expression_Trees](https://charlesreid1.com/wiki/Expression_Trees)
 		- Another, more lightweight implementation of trees
-		- Important thing is not to have the fanciest implementation, but to have one that is fast and that works for your application.
+		- The important thing is not to have the fanciest implementation, but to have one that is fast and that works for your application.
 		- Example: implementing a stack node alone, rather than a full stack object, made it really fast to add and remove things.
 - Sorted trees:
 	- Not covered in the Goodrich book...??
 	- See Skiena for coverage...
 	- Weiss C++ book also has good coverage.
-	- Sorted trees means balanced trees, and balanced trees introduces myriad strategies.
+	- Sorted trees means balanced trees
+	- Balanced trees introduces myriad strategies.
 
 ---
 
@@ -244,9 +234,9 @@ Table of Contents:
 - Timing Notes:
 	- Spent a lot of time wrestling with the sorted and unsorted implementations. The unsorted was *way* slower than expected.
 	- Not sure what's going on. Need to go through and implement them according to the book. 
-	- Finally got classes worked out, 6/22. Better-documented process. Documentation could still use some improvement. Consolidation still an issue.
+	- Finally got classes worked out, 6/22. 
+	- Better-documented process. Documentation could still use some improvement. Consolidation still an issue.
 	- Package? Thinking like you are building an API. Maven. 
-- End of chapter questions:
 - Git Code:
 	- Non-tree sorted/unsorted priority queues: use a built-in list data type
 	- [https://charlesreid1.com:3000/cs/java/src/master/priority-queues/AbstractPriorityQueue.java](https://charlesreid1.com:3000/cs/java/src/master/priority-queues/AbstractPriorityQueue.java)
@@ -257,17 +247,23 @@ Table of Contents:
 ---
 
 
-[ ] Trees: heap trees
+[X] Trees: heap trees
 - 06/23
 - Books:
 	- Goodrich Python/Java books covering priority queue theory/concepts
 - Online videos:
 	- [Heaps and heap sort (MIT 6.006)](https://www.youtube.com/watch?v=B7hVxCmfPtM)
 - Wiki notes:
-	- Binary search trees
-	- Heap sort
+	- Java Priority queues: [https://charlesreid1.com/wiki/Priority_Queues/Java](https://charlesreid1.com/wiki/Priority_Queues/Java)
+	- Priority queue ADT: [https://charlesreid1.com/wiki/Priority_Queues/ADT](https://charlesreid1.com/wiki/Priority_Queues/ADT)
+	- Priority queue (stored in sorted order): [https://charlesreid1.com/wiki/Priority_Queues/Sorted](https://charlesreid1.com/wiki/Priority_Queues/Sorted)
+	- Priority queue (stored in unsorted order): [https://charlesreid1.com/wiki/Priority_Queues/Unsorted](https://charlesreid1.com/wiki/Priority_Queues/Unsorted)
+	- Heaps: [https://charlesreid1.com/wiki/Priority_Queues/Heap](https://charlesreid1.com/wiki/Priority_Queues/Heap)
+	- Heaps with Java: [https://charlesreid1.com/wiki/Priority_Queues/Java](https://charlesreid1.com/wiki/Priority_Queues/Java)
+	- Custom comparators with priority queues: [https://charlesreid1.com/wiki/Priority_Queues/Comparators](https://charlesreid1.com/wiki/Priority_Queues/Comparators)
 - End of chapter questions:
-- Git Code
+	- max oriented priority queue: [https://charlesreid1.com/wiki/Maximum_Oriented_Priority_Queue](https://charlesreid1.com/wiki/Maximum_Oriented_Priority_Queue)
+	- stack implementation of pq: [https://charlesreid1.com/wiki/Priority_Queues/Stack](https://charlesreid1.com/wiki/Priority_Queues/Stack)
 
 
 
@@ -345,7 +341,7 @@ Table of Contents:
 	- [B-Trees insertion and sort](https://www.youtube.com/watch?v=k5J9M5_IMzg)
 - Wiki notes:
 	- Binary search trees [https://charlesreid1.com/wiki/Binary_Search_Trees](https://charlesreid1.com/wiki/Binary_Search_Trees)
-	- Binary search tree navigation [
+	- Binary search tree navigation 
 	- Binary search tree insertion and deletion
 	- OOP: Hooks, virtual method alternatives, positions vs nodes, key-value pairs
 	- AVL search tree
@@ -359,12 +355,55 @@ Table of Contents:
 <a name="graphs"></a>
 ### Graphs
 
-[ ] Graphs: directed and undirected
+[ ] Graphs
+- Books:
+	- Goodrich Chapter 14
+- Wiki notes:
+	- Graph theory:
+		- Definitions: [https://charlesreid1.com/wiki/Graphs/Definitions](https://charlesreid1.com/wiki/Graphs/Definitions)
+		- Matching: [https://charlesreid1.com/wiki/Graphs/Matching](https://charlesreid1.com/wiki/Graphs/Matching)
+		- Connectivity: [https://charlesreid1.com/wiki/Graphs/Connectivity](https://charlesreid1.com/wiki/Graphs/Connectivity)
+		- First theorem of graph theory: [https://charlesreid1.com/wiki/First_Theorem_of_Graph_Theory](https://charlesreid1.com/wiki/First_Theorem_of_Graph_Theory)
+	- Implementations:
+		- Data structures: [https://charlesreid1.com/wiki/Graphs/Data_Structures](https://charlesreid1.com/wiki/Graphs/Data_Structures)
+			- Adjacency matrix:
+			- Adjacency list: 
+			- Adjacency map: [https://charlesreid1.com/wiki/Graphs/Java/Adjacency_Map](https://charlesreid1.com/wiki/Graphs/Java/Adjacency_Map)
+			- Edge list: 
+		- Guava: [https://charlesreid1.com/wiki/Graphs/Guava](https://charlesreid1.com/wiki/Graphs/Guava)
+	- Algorithms:
+		- Traversal: [https://charlesreid1.com/wiki/Graphs/Traversal](https://charlesreid1.com/wiki/Graphs/Traversal)
+		- BFS: [https://charlesreid1.com/wiki/Graphs/Breadth_First_Traversal](https://charlesreid1.com/wiki/Graphs/Breadth_First_Traversal)
+		- DFS: [https://charlesreid1.com/wiki/Graphs/Depth_First_Traversal](https://charlesreid1.com/wiki/Graphs/Depth_First_Traversal)
+		- Finding cycles: [https://charlesreid1.com/wiki/Graphs/Finding_Cycles](https://charlesreid1.com/wiki/Graphs/Finding_Cycles)
+		- Connected components: [https://charlesreid1.com/wiki/Graphs/Finding_Connected_Components](https://charlesreid1.com/wiki/Graphs/Finding_Connected_Components)
+		- Reachability: [https://charlesreid1.com/wiki/Graphs/Reachability](https://charlesreid1.com/wiki/Graphs/Reachability)
+		- Transitive closure: [https://charlesreid1.com/wiki/Graphs/Transitive_Closure](https://charlesreid1.com/wiki/Graphs/Transitive_Closure)
+		- Floyd Warshall: [https://charlesreid1.com/wiki/Graphs/Floyd_Warshall](https://charlesreid1.com/wiki/Graphs/Floyd_Warshall)
+		- Shortest path: [https://charlesreid1.com/wiki/Graphs/Shortest_Path](https://charlesreid1.com/wiki/Graphs/Shortest_Path)
+		- Edge relaxation: [https://charlesreid1.com/wiki/Graphs/Edge_Relaxation](https://charlesreid1.com/wiki/Graphs/Edge_Relaxation)
+		- Dijkstra: [https://charlesreid1.com/wiki/Graphs/Dijkstra](https://charlesreid1.com/wiki/Graphs/Dijkstra)
 
-[ ] Graphs: Adjacency Matrix and List Representations of Graphs 
 
-[ ] Graphs: Traversals (BFS, DFS)
 
+---
+
+
+
+<a name="adv"></a>
+### Skiena: Algorithms, Advanced Data Structures, Programming Challenges
+
+[ ] Advanced Data Structures: Dictionaries, Priority Queues, Binary Trees, Hash Tables
+- 06/02, 06/03
+- Books:
+	- Skiena Chapter 3
+- Wiki notes:
+	- [https://charlesreid1.com/wiki/Dictionaries](https://charlesreid1.com/wiki/Dictionaries)
+	- [https://charlesreid1.com/wiki/Priority_Queues](https://charlesreid1.com/wiki/Priority_Queues)
+
+(This ended up being quite a jump in a different direction. 
+Much more practical focus on algorithms, only the most useful data structures,
+only the core of each data structure, basic operations and big-O analysis.)
 
 
 
@@ -393,49 +432,17 @@ Table of Contents:
 - Search trees study guide - finished 7/9
 	- [https://charlesreid1.com/wiki/Search_Trees_Study_Guide](https://charlesreid1.com/wiki/Search_Trees_Study_Guide)
 
-[ ] Data structures flashcards
 
 
 
----
-
-
-
-<a name="adv"></a>
-### Skiena: Algorithms, Advanced Data Structures, Programming Challenges
-
-[ ] Advanced Data Structures: Dictionaries, Priority Queues, Binary Trees, Hash Tables
-- 06/02, 06/03
-- Books:
-	- Skiena Chapter 3
-- Wiki notes:
-	- [https://charlesreid1.com/wiki/Dictionaries](https://charlesreid1.com/wiki/Dictionaries)
-	- [https://charlesreid1.com/wiki/Priority_Queues](https://charlesreid1.com/wiki/Priority_Queues)
-- End of chapter questions:
-	- Skiena chapter 3 question solutions on wiki
-
-(This ended up being quite a jump in a different direction. 
-Much more practical focus on algorithms, only the most useful data structures,
-only the core of each data structure, basic operations and big-O analysis.)
-
 
 
 <a name="lib"></a>
 ## Data Structures Libraries
 
 Some libraries that provide data structures in Java.
-
-### Guava
-
-[ ] Google Guava Library
-
----
-
-### Apache Commons
-
-[ ] Apache Commons Library
-
----
+* Guava - [https://charlesreid1.com/wiki/Graphs/Guava](https://charlesreid1.com/wiki/Graphs/Guava)
+* Apache Commons
 
 
 
@@ -611,21 +618,15 @@ Slower:
 
 (For full list, see CS flag on wiki)
 
-[ ] Interfaces, Abstract Classes, Virtual Methods
-
-[ ] Interfaces
-
-[ ] Testing (Unit testing)
-
-[ ] Timing
-
-[ ] Memory Usage
-
-[ ] Garbage Collection
-
-[ ] Lambda functions
-
-[ ] Decorators
+Java topics:
+* Interfaces, Abstract Classes, Virtual Methods
+* Interfaces
+* Testing (Unit testing)
+* Timing
+* Memory Usage
+* Garbage Collection
+* Lambda functions
+* Decorators
 
 
 
@@ -743,3 +744,91 @@ Solutions to Google Code Jam problems:
 
 [https://charlesreid1.com:3000/charlesreid1/code-jam](https://charlesreid1.com:3000/charlesreid1/code-jam)
 
+
+
+
+
+
+
+
+
+
+
+<a name="interview-notes"></a>
+## Engineering Interview Notes
+
+Link: [https://www.youtube.com/watch?v=ko-KkSmp-Lk](https://www.youtube.com/watch?v=ko-KkSmp-Lk)
+
+Algorithms:
+* Discuss space and time complexity
+* System design and OOP
+
+Resume:
+* Be prepared to prove what is on your resume
+
+Design questions:
+* Work with your interviewer
+
+Analysis questions:
+* Ensure you understand all aspects of the problem
+* Give multiple solutions
+
+Code questions:
+* Be able to come up with efficient code in a short amount of time
+
+Coding:
+* Be familiar with at least one coding language (C++ or Java)
+* APIs
+* OO design
+* How to test
+* Corner cases and edge cases
+
+Algorithms:
+* Time and space complexity
+* How to improve or change
+
+Data structures:
+* As many as humanly possible
+
+Testing:
+* Unit testing
+* Corner cases, edge cases
+* End to end integration tests
+* Security tests
+
+NP Complete
+* What does NP complete actually *mean*?
+* TSP
+* Knapsack problem
+* Recognize these when they are presented in alternate forms
+
+Math:
+* Discrete math problems
+* Counting, probability, combinatorics
+
+Recursion:
+* Practice
+
+Operating systems:
+* Processes, threads, concurrency issues
+* Semaphores, mutexes, locks
+* Resource allocation
+* Context switching - an issue with the operating system and underlying hardware
+* Scheduling
+
+System design:
+* Knowledge, theory, judgement for real world code
+* Class hierarchies, distributed systems, design of systems under constraints
+
+The Internet:
+* Routers, domains, servers, load balancers, firewalls
+* How search works
+
+Tips:
+* Explain and clarify - even if discarding ideas, vocalize the process
+* Clarification: "Are there time or space complexity requirements?"
+* Keep thinking through the problem - the first solution is not the best, so come up with more 
+* Practice physically writing your code
+* Should be bug free
+
+

ThePlan.md

@@ -58,8 +58,5 @@ Code:
 - [C](https://git.charlesreid1.com/cs/c)
 - [C++](https://git.charlesreid1.com/cs/cpp)
 
-Practice writing out on a whiteboard and/or on paper, 
-before implementing on computer.
-Get a big drawing pad from the art store.