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🦜🔗 Build context-aware reasoning applications
The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
The fastai book, published as Jupyter Notebooks
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…
A small set of Python functions to draw pretty maps from OpenStreetMap data. Based on osmnx, matplotlib and shapely libraries.
Dopamine is a research framework for fast prototyping of reinforcement learning algorithms.
Learn ML engineering for free in 4 months!
A collection of pre-trained, state-of-the-art models in the ONNX format
Portfolio and risk analytics in Python
From the basics to slightly more interesting applications of Tensorflow
Reference models and tools for Cloud TPUs.
Create delightful software with Jupyter Notebooks
Financial portfolio optimisation in python, including classical efficient frontier, Black-Litterman, Hierarchical Risk Parity
Accompanying source code for Machine Learning with TensorFlow. Refer to the book for step-by-step explanations.
Language-Agnostic SEntence Representations
A sequence of Jupyter notebooks featuring the "12 Steps to Navier-Stokes" http://lorenabarba.com/
Performance analysis of predictive (alpha) stock factors
Introduction to Deep Neural Networks with Keras and Tensorflow
Simple chat program that communicates using inaudible sounds
A high performance implementation of HDBSCAN clustering.
An interactive book on deep learning. Much easy, so MXNet. Wow. [Straight Dope is growing up] ---> Much of this content has been incorporated into the new Dive into Deep Learning Book available at …
Implementing a Neural Network from Scratch
2-2000x faster ML algos, 50% less memory usage, works on all hardware - new and old.
Dense image captioning in Torch
A toolkit for controlling Euro Truck Simulator 2 with python to develop self-driving algorithms.
PyTorch implementation of Soft Actor-Critic (SAC), Twin Delayed DDPG (TD3), Actor-Critic (AC/A2C), Proximal Policy Optimization (PPO), QT-Opt, PointNet..
Tensorflow code for the Bayesian GAN (https://arxiv.org/abs/1705.09558) (NIPS 2017)