alexandertyan Goto Github PK

500-ai-machine-learning-deep-learning-computer-vision-nlp-projects-with-code

500 AI Machine learning Deep learning Computer vision NLP Projects with code

ai-expert-roadmap

Roadmap to becoming an Artificial Intelligence Expert in 2022

ana500

McDaniel College MS in Analytics Coursework

ana505

ANA 505 Foundations in Data Mining

ana515_public

For HW submissions

artificial-intelligence-deep-learning-machine-learning-tutorials

A comprehensive list of Deep Learning / Artificial Intelligence and Machine Learning tutorials - rapidly expanding into areas of AI/Deep Learning / Machine Vision / NLP and industry specific areas such as Climate / Energy, Automotives, Retail, Pharma, Medicine, Healthcare, Policy, Ethics and more.

awesome-artificial-intelligence-guidelines

This repository aims to map the ecosystem of artificial intelligence guidelines, principles, codes of ethics, standards, regulation and beyond.

awesome-datascience

:memo: An awesome Data Science repository to learn and apply for real world problems.

aws-workshop

Materials for an introductory AWS Workshop in Large Scale Data Methods - Fall 2018

backoff

Python library providing function decorators for configurable backoff and retry

bigsurvtext

Introduction to Computational Text Analysis at BigSurv 2018

bogdan_state

calculatorlibrary

A repo to test Continuous Integration techniques

causalinf

This the repository for the Spring Causal Inference Course

cmsc_12300_project

d2l-en

Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 300 universities from 55 countries including Stanford, MIT, Harvard, and Cambridge.

dask

Parallel computing with task scheduling

dask-tutorial

Dask tutorial

data-science

:bar_chart: Path to a free self-taught education in Data Science!

data-science-interviews

Data science interview questions and answers

data-science-learning-path

Data Science Learning Path - A complete guide to learn data science for beginners

deep-learning-with-python-notebooks

Jupyter notebooks for the code samples of the book "Deep Learning with Python"

dnwr-zlb

Source code for my second-year paper

dowhy

DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.

econml

ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.

facebookpublicposts

getsocrata

A library for the Socrata Open Data API (SODA)

hello-world

ANA 505 Test Repo

introduction_to_statistical_learning_summary_python

Summary of each chapter of the book- Introduction of Statistical Learning (ISL), along with Python code & data.

introtodeeplearning

Lab Materials for MIT 6.S191: Introduction to Deep Learning