ahafftka Goto Github PK
Name: Ariel Hafftka
Type: User
Ariel Hafftka's Projects
aas
Code to accompany Advanced Analytics with Spark from O'Reilly Media
adversarial_examples_tf2
A beginner-friendly adversarial attacks and defenses library in Tensorflow 2.0
agents
TF-Agents is a library for Reinforcement Learning in TensorFlow
awesome-deep-learning-papers
The most cited deep learning papers
awesome-machine-learning
A curated list of awesome Machine Learning frameworks, libraries and software.
bullet3
Bullet Physics SDK: real-time collision detection and multi-physics simulation for VR, games, visual effects, robotics, machine learning etc.
caffe
Caffe: a fast open framework for deep learning.
caffe-tutorial
DIY Deep Learning for Vision: a Hands-On Tutorial with Caffe
causal-inference
Materials Collection for Causal Inference
coursera
Quiz & Assignment of Coursera
cpython
The Python programming language
data-science-blogs
A curated list of data science blogs
data-science-resources
Data Source Resources - To Be Expanded
dqn
Lua/Torch implementation of DQN (Nature, 2015)
drl-agents
research and implementations of Deep RL agents and their applications
ensemble_amazon
Code to share different ensemble techniques with focus on meta-stacking , using data from Amazon.com - Employee Access Challenge kaggle competition
graphembedding
Implementation and experiments of graph embedding algorithms.
graphneuralnetwork
Implementation and experiments of graph neural netwokrs, like gcn,graphsage,gat,etc.
keras
Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on Theano or TensorFlow.
keras-rl
Deep Reinforcement Learning for Keras.
lil-log
Lilian's Blog
minerva
Minerva: a fast and flexible tool for deep learning on multi-GPU. It provides ndarray programming interface, just like Numpy. Python bindings and C++ bindings are both available. The resulting code can be run on CPU or GPU. Multi-GPU support is very easy.
mlalgorithms
Minimal and clean examples of machine learning algorithms
mlr
mlr: Machine Learning in R
mxnet
Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more
mxnet-notebooks
Notebooks for MXNet
neural
neural networks, sparse encoders, and recursive auto encoder sin python
nnvm
Intermediate Computational Graph Representation for Deep Learning Systems
numerical-tours
Numerical Tours of Signal Processing
pattern_classification
A collection of tutorials and examples for solving and understanding machine learning and pattern classification tasks
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