chanddu Goto Github PK

analytics-using-spark-and-hbase

android

android

backgammon-python-numpy-

Implemented a expectiminimax agent (2-ply search) with alpha – beta pruning and forward pruning (to reduce the branching factor in the game tree) to determine the best move give the state of the board.

book-search-engine

Search Engine for Books (Java, Apache Lucene, crawler4j, Apache Spark)

bootstrap-datetimepicker

Date/time picker widget based on twitter bootstrap

chanddu.github.io

classifying-hand-written-digits-mnist-dataset-

Trained a feedforward network via backpropagation – L2 regularized logistic cost function, sigmoid activation function Obtained a training accuracy of 97.59% and a test accuracy of 95.62

client-server-in-c-cpp

Implemented basic client server with C and C++ constructs together with password sha1 encryption and messages aes encryption

college-s5

All S5 courses (only electives taken by me DAA,NTC)

compilers-lab

NIT,Calicut Compilers Lab course

copart-learning

Sample React and redux project done at copart

cs-144

CS144 Stanford

ctci-6th-edition-python

Cracking the Coding Interview 6th Ed. Python Solutions

detect_insults

devconnector

Social Network Application (Node, Express, MongoDB)

docker-airflow

Docker Apache Airflow

ds-lab

dsa-java

All DSA Assignments in JAVA

face-recognition

Face Recognition library

faceexperiments

guide_python

Python Programming Guide.

hackerrank

HackerRank Practice problems

karateclub

A general purpose community detection and network embedding library for research built on NetworkX.

linux-sysadmin-interview-questions

Collection of linux sysadmin/devop interview questions

machine_learning

Python coded examples and documentation of machine learning algorithms.

minix

Understanding Minix Operating System

movie-recommender-system

Recommender System (Java, Apache Spark)

nlp

Sentimental-Analysis

os-lab-nitc

Lab until Stage 11

part-of-speech-tagging-with-discriminatively-re-ranked-hidden-markov-models

Implemented POS tagging by combining a standard HMM tagger separately with a Maximum Entropy classifier designed to re-rank the k-best tag sequences produced by HMM – achieved better results than VITERBI (decoding algorithm)