6875 Open source projects that are alternatives of or similar to Neural Tangents

A collection of Bayesian data analysis recipes using PyMC3

Machine learning, in numpy

Code for "A-NICE-MC: Adversarial Training for MCMC"

Computations and statistics on manifolds with geometric structures.

How to do Bayesian statistical modelling using numpy and PyMC3

Awesome Artificial Intelligence, Machine Learning and Deep Learning as we learn it. Study notes and a curated list of awesome resources of such topics.

An introductory series to Reinforcement Learning (RL) with comprehensive step-by-step tutorials.

🎨 Artistic neural style transfer with tweaks (pytorch).

PyMC3 educational resources

This toolbox is support material for the book on CNN (http://www.convolution.network).

A lightweight, multi-tenant, scalable and secure gateway that enables Jupyter Notebooks to share resources across distributed clusters such as Apache Spark, Kubernetes and others.

A simple probabilistic programming language.

Lab Materials for MIT 6.S191: Introduction to Deep Learning

This repository contains my full work and notes on Coursera's NLP Specialization (Natural Language Processing) taught by the instructor Younes Bensouda Mourri and Łukasz Kaiser offered by deeplearning.ai

Support content for my blog

머신러닝 입문자 혹은 스터디를 준비하시는 분들에게 도움이 되고자 만든 repository입니다. (This repository is intented for helping whom are interested in machine learning study)

Python package for computing the Curie depth from the magnetic anomaly

Doing Bayesian Data Analysis, 2nd Edition (Kruschke, 2015): Python/PyMC3 code

This repository stores the files used for my summer internship's work on "teacher-student learning", an experimental method for training deep neural networks using a trained teacher model.

🎓 Educational application of Hidden Markov Model to Autonomous Driving 🚕🚙🚗

Succinct Machine Learning algorithm implementations from scratch in Python, solving real-world problems (Notebooks and Book). Examples of Logistic Regression, Linear Regression, Decision Trees, K-means clustering, Sentiment Analysis, Recommender Systems, Neural Networks and Reinforcement Learning.

Official Repsoitory for "Mish: A Self Regularized Non-Monotonic Neural Activation Function" [BMVC 2020]

Visualisations for Convolutional Neural Networks in Pytorch

Deep Learning over PyTorch

NIPS 2017: ALICE: Towards Understanding Adversarial Learning for Joint Distribution Matching

Variational autoencoders for collaborative filtering

Repo for the Deep Reinforcement Learning Nanodegree program

由淺入深的深度學習資源 Collection of deep learning materials for everyone

Contains my explorations of TensorFlow 2.x

Image augmentation library in Python for machine learning.

brief introduction to Python for neural networks

Koç University deep learning framework.

Deep Learning Specialization by Andrew Ng on Coursera.

Keras tutorial for beginners (using TF backend)

TensorFlow 101: Introduction to Deep Learning for Python Within TensorFlow

Machine Learning tutorials with TensorFlow 2 and Keras in Python (Jupyter notebooks included) - (LSTMs, Hyperameter tuning, Data preprocessing, Bias-variance tradeoff, Anomaly Detection, Autoencoders, Time Series Forecasting, Object Detection, Sentiment Analysis, Intent Recognition with BERT)

Bayesian Data Analysis demos for Python

A probabilistic programming language in TensorFlow. Deep generative models, variational inference.

Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more

Daily Dose of Neural Network that Everyone Needs

Aspect-Based Sentiment Analysis

Amazon Forest Computer Vision: Satellite Image tagging code using PyTorch / Keras with lots of PyTorch tricks

Jupyter magics and kernels for working with remote Spark clusters

This contains a number of IP[y]: Notebooks that hopefully give a light to areas of bayesian machine learning.

Python package for learning the graphical structure of Bayesian networks, parameter learning, inference and sampling methods.

Adventure into using multi attention recurrent neural networks for time-series (city traffic) for the 2017-11-18 McKinsey IronMan (24h non-stop) prediction challenge

Deep Kernel Learning. Gaussian Process Regression where the input is a neural network mapping of x that maximizes the marginal likelihood

This is just a collection of projects that made during my DEEPLEARNING NANODEGREE by UDACITY

Books, papers and links to latest research in ML/AI

Notebooks about Bayesian methods for machine learning

Pharmaceutical Modeling and Simulation for Nonlinear Mixed Effects (NLME), Quantiative Systems Pharmacology (QsP), Physiologically-Based Pharmacokinetics (PBPK) models mixed with machine learning

Tutorials, assignments, and competitions for MIT Deep Learning related courses.

Example PyMC3 project for performing Bayesian data analysis using a probabilistic programming approach to machine learning.

PyTorch implementation of "Transparency by Design: Closing the Gap Between Performance and Interpretability in Visual Reasoning"

This repository contains Ipython notebooks and datasets for the data analytics youtube tutorials on The Semicolon.

Udacity Self-Driving Car Engineer Nanodegree. Project: Build a Traffic Sign Recognition Classifier

Code for the Lovász-Softmax loss (CVPR 2018)