Exercises for the book Artificial Intelligence: A Modern Approach

Pseudocode descriptions of the algorithms from Russell And Norvig's "Artificial Intelligence - A Modern Approach"

Python implementation of algorithms from Russell And Norvig's "Artificial Intelligence - A Modern Approach"

client for https://ammobin.ca

T81-558: PyTorch - Applications of Deep Neural Networks @Washington University in St. Louis

Drawing a smart dart art. If you are less artistic, use commands, based on the Logo programming language for children, to learn basic programming concepts by drawing.

📚 List of awesome university courses for learning Computer Science!

🍺 The missing package manager for macOS (or Linux)

A framework for evaluating community mining algorithms.

CUDA implementation of Tractable Approximate Gaussian Inference

dartling is a domain model framework

Cheat Sheets

Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!

Detection of Accounting Anomalies using Deep Autoencoder Neural Networks - A lab we prepared for NVIDIA's GPU Technology Conference 2018 that will walk you through the detection of accounting anoma…

EX08

Mirror of Apache Hadoop

Natural Language Toolkit for Indic Languages aims to provide out of the box support for various NLP tasks that an application developer might need

Rmd source files for the HarvardX series PH525x

Large-scale linear classification, regression and ranking in Python

Programming assignments from Coursera's Machine Learning course taught by Andrew Ng.

This repo is specially created for all the work done my me as a part of Coursera's Machine Learning Course.

Python codes for common Machine Learning Algorithms