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atari-rl

Atari - Deep Reinforcement Learning algorithms in TensorFlow

automl

Deep Reinforcement Learning for Efficient Neural Architecture Search (ENAS) in PyTorch, i.e., AutoML. Code based on the paper https://arxiv.org/abs/1802.03268

automl-in-action-notebooks

Jupyter notebooks for the code samples of the book "Automated Machine Learning in Action"

cmudeeplens

Deep learning strong lens finder

conda-cuda

Guide to install cuda and cudnn with Anaconda

deep-reinforcement-learning

Repo for the Deep Reinforcement Learning Nanodegree program

deep-rl-time-series

Playing trading games with deep reinforcement learning

deep_reinforcement_learning_course

Implementations from the free course Deep Reinforcement Learning with Tensorflow and PyTorch

deeplense

deeprl-tensorflow2

🐋 Simple implementations of various popular Deep Reinforcement Learning algorithms using TensorFlow2

get-started-with-jax

The purpose of this repo is to make it easy to get started with JAX, Flax, and Haiku. It contains my "Machine Learning with JAX" series of tutorials (YouTube videos and Jupyter Notebooks) as well as the content I found useful while learning about the JAX ecosystem.

gigalens

Gradient Informed, GPU Accelerated Lens modelling (GIGALens) -- a package for fast Bayesian inference on strong gravitational lenses.

github-for-developers

gravitational-lensing

Gravitational lensing course

jax

JAX

lens-detector

lensfinder-euclid

Binary classifier with convolutional neural network

lenstronomy-tutorials

Extension modules to the lenstronomy software package

lexactum

LEXACTUM (Lens EXtrActor CaTania University of Malta) was developed to explore new solutions for the Gravitational Lens Finding Challenge 1.0 (http://metcalf1.difa.unibo.it/blf-portal/gg_challenge.html), primarily those based on Convolutional Neural Networks (CNNs).

machine-learning-engineering-for-production-public

Public repo for DeepLearning.AI MLEP Specialization

ml-agents

The Unity Machine Learning Agents Toolkit (ML-Agents) is an open-source project that enables games and simulations to serve as environments for training intelligent agents using deep reinforcement learning and imitation learning.

ml-in-cosmology

A comprehensive list of published machine learning applications to cosmology

ml-notebooks

Colab/Jupyter noteboks on machine learning

nas-with-code

Neural Architecture Search (NAS) papers with code

neural-subhalo-slope-data

Code for "Subhalo effective density slope measurements from HST strong lensing data with neural likelihood-ratio estimation"

nni

An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.

ovejero

Conducts hierarchical inference of strongly-lensed systems with Bayesian neural networks

paltas

Conduct simulation-based inference on strong gravitational lensing systems.

parlange.github.io

github.io | parlange

ray

Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a toolkit of libraries (Ray AIR) for accelerating ML workloads.