6583 Open source projects that are alternatives of or similar to Hamiltonian Nn

An electronic simulation library written in pure Python

A Julia package for Gaussian Processes

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General Assembly's Data Science course in Washington, DC

Observations and notes to understand the workings of neural network models and other thought experiments using Tensorflow

点睛 - 头条号文章标题生成工具 （Dianjing, AI to write Title for Articles）

Decentralized Machine Learning Client

Official PyTorch Implementation for "Rotate to Attend: Convolutional Triplet Attention Module." [WACV 2021]

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This is the code for "Bitcoin Prediction" by Siraj Raval on Youtube

This trading-gym is the first trading for agent to train with episode of short term trading itself.

Python version of Quantiacs toolbox and sample trading strategies

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Framework for Multi-Agent Deep Reinforcement Learning in Poker

NAS-FPN: Learning Scalable Feature Pyramid Architecture for Object Detection.

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A crash course in six episodes for software developers who want to become machine learning practitioners.

Library extending Jupyter notebooks to integrate with Apache TinkerPop and RDF SPARQL.

Full Stack Data Science in Python

Python code for the fast bilateral solver

A python package that includes many methods for decoding neural activity

Python/Keras implementation of integrated gradients presented in "Axiomatic Attribution for Deep Networks" for explaining any model defined in Keras framework.

Self hosted alternative to Google Photos

Weakly Supervised Segmentation with Tensorflow. Implements instance segmentation as described in Simple Does It: Weakly Supervised Instance and Semantic Segmentation, by Khoreva et al. (CVPR 2017).

Text detection model that combines Retinanet with textboxes++ for OCR

Distributed Tensorflow, Keras and PyTorch on Apache Spark/Flink & Ray

Python solutions to solve practical business problems.

Implementation of Deep Deterministic Policy Gradients using TensorFlow and OpenAI Gym

Seed, Expand, Constrain: Three Principles for Weakly-Supervised Image Segmentation

Repository for coursera specialization Applied Data Science with Python by University of Michigan

《统计学习方法》（第一版）习题解答，在线阅读地址：https://datawhalechina.github.io/statistical-learning-method-solutions-manual

A tutorial for MNIST handwritten digit classification using sklearn, PyTorch and Keras.

Deep Learning examples with Keras.

Auxiliary Classifier Generative Adversarial Networks in Keras

Code and Dataset for CVPR2020 "Dynamic Refinement Network for Oriented and Densely Packed Object Detection"

Python tutorials for introduction to machine learning

Natural Language Processing with TensorFlow, published by Packt

Everything I know

Example of "biological" learning for MNIST

Detect text in natural images with SSD, Single Shot Detection

Deep learning codes and projects using Python

Some practices about deep learning

Code for NeurIPS 2019 paper: "Tensor Programs I: Wide Feedforward or Recurrent Neural Networks of Any Architecture are Gaussian Processes"

主要存储Datawhale组队学习中“推荐系统”方向的资料。

Repositório para armazenamento de código e notebooks de postagens do blog e cursos.

A beginner-friendly project to help you in open-source contributions. Made specifically for contributions in HACKTOBERFEST 2020! Hello World Programs and Algorithms! Please leave a star ⭐ to support this project! ✨

Pytorch version of Realtime Multi-Person Pose Estimation project

CardIO is a library for data science research of heart signals

Implemented digit detector in natural scene using resnet50 and Yolo-v2. I used SVHN as the training set, and implemented it using tensorflow and keras.

Russian language models for spaCy

An example attention network with simple dataset.

Tutorial demonstrating how to create a semantic segmentation (pixel-level classification) model to predict land cover from aerial imagery. This model can be used to identify newly developed or flooded land. Uses ground-truth labels and processed NAIP imagery provided by the Chesapeake Conservancy.

PyTorch implementation of VQ-VAE by Aäron van den Oord et al.

Multi-hop knowledge graph reasoning learned via policy gradient with reward shaping and action dropout

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