Adrian Plattner's starred repositories
every-programmer-should-know
A collection of (mostly) technical things every software developer should know about
ML-From-Scratch
Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.
reinforcement-learning
Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.
reinforcement-learning-an-introduction
Python Implementation of Reinforcement Learning: An Introduction
awesome-rl
Reinforcement learning resources curated
python-machine-learning-book-2nd-edition
The "Python Machine Learning (2nd edition)" book code repository and info resource
ISLR-python
An Introduction to Statistical Learning (James, Witten, Hastie, Tibshirani, 2013): Python code
deep-reinforcement-learning-papers
A list of recent papers regarding deep reinforcement learning
kaggle-web-traffic
1st place solution
Kaggle-Ensemble-Guide
Code for the Kaggle Ensembling Guide Article on MLWave
data-science-interview-questions-and-answers
Data science interview questions with answers. Not ideally (yet)
fancyimpute
Multivariate imputation and matrix completion algorithms implemented in Python
burner-email-providers
A list of temporary email providers
Coursera-Machine-Learning
Coursera Machine Learning - Python code
pytorch-maml-rl
Reinforcement Learning with Model-Agnostic Meta-Learning in Pytorch
instacart-basket-prediction
Kaggle | Instacart Market Basket Analysis🥕🥉
meta-learning-lstm
This repo contains the source code accompanying a scientific paper with the same name.
google-interview-university
A complete daily plan for studying to become a Google software engineer.
sift-python
Sift API (Python client)