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6.00.2x

MITx: 6.00.2x Introduction to Computational Thinking and Data Science

aind-dl

aj_ml_library

This library is a wrapper for sklearn and works with data stored using Pandas module.

algorithm-implementations

Share, discuss and learn about algorithm implementations!

annotated_research_papers

This repo contains annotated research papers that I found really good and useful

artificial-intelligence

Interesting Artificial Intelligence Projects

asu_cse_575

awesome-python

A curated list of awesome Python frameworks, libraries, software and resources

awesome-recsys-papers

The awesome and classic papers in recommendation system!!! Good luck to every RecSys-learner!

awesome-tensorflow

TensorFlow - A curated list of dedicated resources http://tensorflow.org

berkeley-stat-157

Homepage for STAT 157 at UC Berkeley

books

c-programming

c-programming-1

Code worked on for Duke's Intro to Programming in C course

char-rnn

Multi-layer Recurrent Neural Networks (LSTM, GRU, RNN) for character-level language models in Torch

chefbot_ros_pkg

This is ROS package mentioned in the book "Learning Robotics using Python". This package contain drivers, Launch files for working with Chefbot, mentioned on this book|New version of code for ROS Kinetic: https://github.com/PacktPublishing/Learning-Robotics-using-Python-Second-Edition

cisco-ios-xe-postman-collections

Postman collections for Cisco IOS XE

coach

Reinforcement Learning Coach by Intel AI Lab enables easy experimentation with state of the art Reinforcement Learning algorithms

codesamples

CBT Nuggets course code samples

complete-python-3-bootcamp

Course Files for Complete Python 3 Bootcamp Course on Udemy

comsw4721_machinelearning_homework

Implementation of Machine Learning algorithms using numpy in Python. The exercise was done as part of homeworks given at Columbia's Machine Learning (COMS W4721) class conducted by Dr. John Paisley

coursera-machine-learning

Coursera Machine Learning - Python code

coursera-machine-learning-stanford

Machine learning-Stanford University

cqa_analysis

Course project for CSE 575 (Statistical Machine Learning)

credit-card-fraud-detection-using-autoencoders-in-keras

iPython notebook and pre-trained model that shows how to build deep Autoencoder in Keras for Anomaly Detection in credit card transactions data

cs224d-deep-learning-for-nlp-stanford

Solutions to the programming assignments of Stanford's deep learning class offered at Stanford. 224D (2016)

cs236605-tutorials

cse575--statistical-machine-learning

ASU Course Work CSE 575 Statistical Machine Learning

cufflinks

Productivity Tools for Plotly + Pandas

d2l-en

Dive into Deep Learning: an interactive deep learning book with code, math, and discussions