odecamsiul Goto Github PK

aiproj_humordetector

anatomyofmatplotlib

Anatomy of Matplotlib -- tutorial developed for the SciPy conference

arteagac.github.io

Personal Website

automated-feature-engineering

Automated feature engineering in Python with Featuretools

automated-manual-comparison

Automated vs Manual Feature Engineering Comparison. Implemented using Featuretools.

awesome-interpretable-machine-learning

awesome-rl

Reinforcement learning resources curated

cartpole

OpenAI's cartpole env solver.

coinrun-game-ai-assignment

competitions

Solutions to Recommender Systems competitions

corl2019-drex

Code and project page for D-REX algorithm from the paper "Better-than-Demonstrator Imitation Learning via Automatically-Ranked Demonstrations" presented at CoRL 2019.

cs228-material

Teaching materials for the probabilistic graphical models and deep learning classes at Stanford

d3

Bring data to life with SVG, Canvas and HTML. :bar_chart::chart_with_upwards_trend::tada:

datascience_artificialintelligence_utils

Examples of Data Science projects and Artificial Intelligence use cases

david-silver-reinforcement-learning

Notes for the Reinforcement Learning course by David Silver along with implementation of various algorithms.

deep-active-learning

Deep Active Learning

deep_reinforcement_learning_course

Implementations from the free course Deep Reinforcement Learning with Tensorflow

dive-into-machine-learning

Dive into Machine Learning with Python Jupyter notebook and scikit-learn!

free-programming-books

:books: Freely available programming books

general

SWC-OSG workshop generic materials.

handson-ml

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.

hateval

hmmlearn

Hidden Markov Models in Python, with scikit-learn like API

interpretable-ai-book

Code associated with my Interpretable AI Book (https://www.manning.com/books/interpretable-ai)

introduction_to_ml_with_python

Notebooks and code for the book "Introduction to Machine Learning with Python"

jupyter

Jupyter metapackage for installation, docs and chat

kalman-and-bayesian-filters-in-python

Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.

lime

Lime: Explaining the predictions of any machine learning classifier

machine-learning-project-walkthrough

An implementation of a complete machine learning solution in Python on a real-world dataset. This project is meant to demonstrate how all the steps of a machine learning pipeline come together to solve a problem!

markdown-here

Google Chrome, Firefox, and Thunderbird extension that lets you write email in Markdown and render it before sending.