Deepak Rishi's repositories
Tic-Tac-Toe-Using-Alpha-Beta-Minimax-Search
This code demonstrates the use of Alpha Beta Pruning for Game playing. Since, Tic Tac Toe has a depth of 9 , I use a heuristic function that evaluates the Board State after searching through a depth of 3. The heuristic function calculates the expected score of winning for the PC given the board state.
Decision-Tree-in-Python-for-Continuous-Attributes
This code constructs a Decision Tree for a dataset with continuous Attributes. Each training instance has 16 numeric attributes (features) and a classification label, all separated by commas. In deciding which attribute to test at any point, the information gain metric is used. The node test threshold for each potential attribute is set using this same metric i.e. at each point, all the values that exist for a particular attribute in the remaining instances are ordered, and threshold values that are (half way) between successive attribute values are used to find the Information Gain. The threshold value that gives the highest information gain is used. The same attribute can be tested again later in the tree (with a different threshold).
Hidden-Markov-Model
This Code Implements the Hidden Markov Model (Monitoring and the Viterbi Algorithm) in Python on a Time series Data.
Policy-Search-in-a-Markov-Decision-Process
This code evaluates an optimal policy in a Markov Decision Process. We use a 3x3 Grid World with the Goal State at 3,3 with a reward of 10 and the rest of the non terminal states with a reward of -1.
Bayes-Net-Structure-Prediction
Learning how to predict a Bayes Net Structure of a Dataset
Bernoulli-Document-Model_Based-Naive-Bayes-SMS-Spam-Classification
This code is for Naive Bayes Spam Classification on the SMS Spam Collection Data Set from the UCI Machine Learning Repository.
dl4j-0.4-examples
Please use these examples based on deeplearning4j 0.4.* release.
Logistic-Regression-Convergence-Analysis
This code implements Logistic Regression using Newton's Method in Python.
Non-Linear-Kernelized-Regression
This code implements Non Linear Kernelized Regression using a Gaussian Kernel on a dataset
PacMan
Multi Agent Pacman Berkley 188
setjmp-longjmp-ucontext-snippets
Implementing coroutines, channels, message passing, etc.
t-SNE
This code demonstrates the how to use t-SNE from Scikit -Learn's implementation
tensorflow
Computation using data flow graphs for scalable machine learning
tsp-astar
This code solves the Travelling Salesman Problem using Astar Search. Minimum Spanning Tree Heuristic was used to estimate the remaining distance from one city to the last.
variable-elimination
Variable Elimination for Bayes Net