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2015lab1

applied-methods-phd

Repo for Yale Applied Empirical Methods PHD Course

awesome-courses

:books: List of awesome university courses for learning Computer Science!

awesome-deep-rl

This project is for learning and researching on DRL. This area is so hot that everyday we can see new ideas happen. I would like to give an explicit landscape for deep rl, one reason is for better understanding existed methods and theoretical results, the other is to seek potential developments based on these findings. Any suggestion/improvement is welcomed.

awesome-r

A curated list of awesome R packages, frameworks and software.

awesome-recsys-papers

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

awesome-rl

Reinforcement learning resources curated

awesome-transfer-learning

Best transfer learning and domain adaptation resources (papers, tutorials, datasets, etc.)

bayesian-statistics

Course material for Bayesian and Modern Statistics, STA601, Duke University, Spring 2015.

cevae

Causal Effect Inference with Deep Latent-Variable Models

courses

fast.ai Courses

crowdai-criteo-ad-placement-challenge-starter-kit

Starter kit for getting started in the NIPS 2017 Criteo Ad Placement Challenge

cs231n

data102-fa21-final-proj

Final project for UC Berkeley's Data C102, Fall 2021

data102-final

This is the final project for Data 102 at the University of California, Berkeley. This project was to conduct a guided analysis for a dataset of our choice, selected from 3 major topics (or data of your choice). We chose to work with the transportation data set, as well as the New York Times 'Rolling Averages - US Counties' dataset

dive-into-machine-learning

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

ds-102-book

Textbook for Data 102

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.

fa19

The course content for the fall 2019 iteration of DS-102.

fa21

Public facing repo for Data 100, Fall 2021

fa21-1

Public course content for the Fall 2021 iteration of DS-102

ghostwriter

A port of ghostwriter theme to Hugo.

hd_irf

jekyll-course-website-template

Feature-rich and easy-to-use Jekyll template for the websites of academic courses

kaggle-crowdflower

Kaggle 'Search Results Relevance' 2nd place solution

kaggle_crowdflower

1st Place Solution for Search Results Relevance Competition on Kaggle (https://www.kaggle.com/c/crowdflower-search-relevance)

list_of_recommender_systems

A List of Recommender Systems and Resources

lowrankmodels.jl

LowRankModels.jl is a julia package for modeling and fitting generalized low rank models.

materials-fa21

Data 8 Public Materials for Fall 2021.

medical-data