AhmedLabbaali's repositories
ML_Resouces
This is a not-particularly-systematic attempt to curate a handful of my favorite resources for learning statistics and machine learning. This isn’t meant to be comprehensive, and in fact is still missing the vast majority of my favorite explainers. Rather, it’s just a smattering of resources I’ve found myself turning to multiple times and thus would like to have in one place.
Reinforcement-Learning-in-Finance-
Machine Learning and Reinforcement Learning in Finance, New York University-Tandon School of Engineering.
cvx_short_course
Materials for a short course on convex optimization.
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.
numerical-tours
Numerical Tours of Signal Processing
RL-Adventure
Pytorch Implementation of DQN / DDQN / Prioritized replay/ noisy networks/ distributional values/ Rainbow/ hierarchical RL
RL-Adventure-2
PyTorch0.4 implementation of: actor critic / proximal policy optimization / acer / ddpg / twin dueling ddpg / soft actor critic / generative adversarial imitation learning / hindsight experience replay
Advanced-Machine-Learning-Specialization
Advanced Machine Learning Specialization on Coursera
Color-Switch-Replica
This is the source code for a Color Switch replica created during a Twitch Livestream.
cs231n.github.io
Public facing notes page
Data-Analysis
Data Science Using Python
Data-Analysis-and-Machine-Learning-Projects
Repository of teaching materials, code, and data for my data analysis and machine learning projects.
demo-repo
Demo for Github
introduction_to_ml_with_python
Notebooks and code for the book "Introduction to Machine Learning with Python"
natural-language-processing
Resources for "Natural Language Processing" Coursera course.
nlp_course
YSDA course in Natural Language Processing
pymc3
Probabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with Theano
reinforcement-learning
Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.
scikit-learn-mooc
scikit-learn-mooc
scipy-2018-sklearn
Scipy 2018 scikit-learn tutorial by Guillaume Lemaitre and Andreas Mueller
sklearn_tutorial
Materials for my scikit-learn tutorial
spatial_graph_convnets
PyTorch implementation of residual gated graph ConvNets, ICLR’18
spectral_inference_networks
Implementation of Spectral Inference Networks, ICLR 2019
tensorflow-training
https://www.cscs.ch/events/past-events/event-detail/efficient-and-distributed-training-with-tensorflow-on-piz-daint/
tensorflow-workshop
Slides and code from our TensorFlow workshop.