6327 Open source projects that are alternatives of or similar to Pytorch_exercises

Deep Learning Specialization by Andrew Ng on Coursera.

brief introduction to Python for neural networks

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

Support content for my blog

🛠 All-in-one web-based IDE specialized for machine learning and data science.

Code and data accompanying Natural Language Processing with PyTorch published by O'Reilly Media https://nlproc.info

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.

Example projects I completed to understand Deep Learning techniques with Tensorflow. Please note that I do no longer maintain this repository.

Anomaly detection for temporal data using LSTMs

Unsupervised Scalable Representation Learning for Multivariate Time Series: Experiments

Applying Data Science and Machine Learning to Solve Real World Business Problems

Computations and statistics on manifolds with geometric structures.

Plain python implementations of basic machine learning algorithms

AI for everyone! 🎉 Neural networks, tools and a library we use in Supervisely

Keras tutorial for beginners (using TF backend)

Probabilistic reasoning and statistical analysis in TensorFlow

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

A simple probabilistic programming language.

Image augmentation library in Python for machine learning.

Complete Assignments for CS231n: Convolutional Neural Networks for Visual Recognition

A blog which talks about machine learning, deep learning algorithms and the Math. and Machine learning algorithms written from scratch.

🧑‍🏫 50! Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

Codes for weekly challenges on Deep Learning by Siraj

pytorch 包教不包会

本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为TensorFlow 2.0实现，项目已得到李沐老师的认可

📒 Sphinx source parser for Jupyter notebooks

Papers about deep learning ordered by task, date. Current state-of-the-art papers are labelled.

Lectures on scientific computing with python, as IPython notebooks.

Jupyter notebooks from the scikit-learn video series

This is my assignment on Andrew Ng's course “neural networks and deep learning”

A general-purpose framework for solving problems with machine learning applied to predicting customer churn

Phased LSTM

Curso de Data Science em Português

Using multidimensional LSTM neural networks to create a forecast for Bitcoin price

Python implementation of soft-DTW.

Segmentation models with pretrained backbones. PyTorch.

An open-source, low-code machine learning library in Python

中文版TA-Lib库使用教程

Automated vs Manual Feature Engineering Comparison. Implemented using Featuretools.

Code release for NeRF (Neural Radiance Fields)

This is a tensorflow re-implementation of Feature Pyramid Networks for Object Detection.

COMS W4995 Applied Machine Learning - Spring 19

machine learning/artificial intelligence notes

Python code for "Machine learning: a probabilistic perspective" (2nd edition)

darknet with GIoU

Debugging, monitoring and visualization for Python Machine Learning and Data Science

Materials for Mathematical Tools for Neuroscience course at Harvard (Neurobio 212)

A Python module for computing the Structural Similarity Image Metric (SSIM)

Using deep learning to generate music in MIDI format.

Transformer of "Attention Is All You Need" (Vaswani et al. 2017) by Chainer.

Jupyter notebook integration with Spyder

Python-based tools for document analysis and OCR

A rapid on-ramp primer for programmers who want to learn Python for doing data science research and development.

Semantic Scene Completion from a Single Depth Image

Source code for the MICCAI 2016 Paper "Automatic Liver and Lesion Segmentation in CT Using Cascaded Fully Convolutional NeuralNetworks and 3D Conditional Random Fields"

Image Captioning using InceptionV3 and beam search