Stars
Notes and links from the book club meetings
a visual dictionary of Bayesian Networks and Causal Inference.
Learning Discrete Bayesian Network Classifiers from Data
TRADING ECONOMICS - API Code Examples
A technical report on convolution arithmetic in the context of deep learning
A framework for fluid flow (Reynolds-averaged Navier Stokes) predictions with deep learning
The fastai book, published as Jupyter Notebooks
Ridiculously Uncomplicated macOS Python Statusbar apps
Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
Notebooks for https://python-programming.quantecon.org
Source files for https://python-programming.quantecon.org
AI-Crash-Course, published by Packt
forgeNet: FORest Graph-Embedded deep feedforward NETwork
Converts images into html files
Statistical Rethinking course at MPI-EVA from Dec 2018 through Feb 2019
Implementation for <Large-Margin Softmax Loss for Convolutional Neural Networks> in ICML'16.
Implementation of some classic Machine Learning model from scratch and benchmarking against popular ML library
An Open Source Machine Learning Framework for Everyone
Companion repository to GANs in Action: Deep learning with Generative Adversarial Networks
Code for the book Deep Learning with PyTorch by Eli Stevens, Luca Antiga, and Thomas Viehmann.
⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 or handson-mlp instead.
Repository of code and resources related to different data science and machine learning topics. For learning, practice and teaching purposes.
Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.
Computing the eigenvalues of Neural Tangent Kernel and Conjugate Kernel (aka NNGP kernel) over the boolean cube
The Zenburn colour theme ported to Emacs
Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filte…
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