7465 Open source projects that are alternatives of or similar to Pytorch Lesson Zh

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

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

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

Ever wondered how to code your Neural Network using NumPy, with no frameworks involved?

Tutorials on getting started with PyTorch and TorchText for sentiment analysis.

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

AI-related tutorials. Access any of them for free → https://towardsai.net/editorial

🟣 Object detection of abstract shapes with neural networks

Early stopping for PyTorch

🧑‍🏫 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, ... 🧠

Tutorials on implementing a few sequence-to-sequence (seq2seq) models with PyTorch and TorchText.

My Attempt(s) In The World Of ML/DL....

Tutorial for End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF

A tutorial on how to implement models for part-of-speech tagging using PyTorch and TorchText.

PyTorch 101 series covering everything from the basic building blocks all the way to building custom architectures.

Material for the tutorial: "Deep Diving into GANs: from theory to production"

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

Important paper implementations for Question Answering using PyTorch

Tutorials on how to implement a few key architectures for image classification using PyTorch and TorchVision.

This is code of book "Learn Deep Learning with PyTorch"

코딩셰프의 3분 딥러닝, 케라스맛

top 1% solution to toxic comment classification challenge on Kaggle.

Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).

A stable algorithm for GAN training

Deep learning codes and projects using Python

Tutorial: Web scraping in Python with Beautiful Soup

Anomaly detection for temporal data using LSTMs

A DCGAN that generate Cat pictures 🐱‍💻

All about attention in neural networks. Soft attention, attention maps, local and global attention and multi-head attention.

Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models

My personal notes, presentations, and notebooks on everything Deep Learning.

RadIO is a library for data science research of computed tomography imaging

Tutorials for the Astropy Project

Unsupervised Scalable Representation Learning for Multivariate Time Series: Experiments

Stable-Baselines tutorial for Journées Nationales de la Recherche en Robotique 2019

A clear, concise, simple yet powerful and efficient API for deep learning.

A python tutorial on bayesian modeling techniques (PyMC3)

Deep learning system course

SuperComputing 2017 Deep Learning Tutorial

Temporal Causal Discovery Framework (PyTorch): discovering causal relationships between time series

Quick, visual, principled introduction to pytorch code through five colab notebooks.

A day to day plan for this challenge (50 Days of Machine Learning) . Covers both theoretical and practical aspects

Deep Learning / NLP tutorial for Chatbot Developers

验证码识别

Virtual Clothing Try-on with Deep Learning. PyTorch reproduction of SwapNet by Raj et al. 2018. Now with Docker support!

Deep Learning Zero to All - Tensorflow

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.

Open-Source Tutorial For Analyzing and Visualizing Cryptocurrency Data

[tutorial]A functional, Data Science focused introduction to Python

Simple Implementation of many GAN models with PyTorch.

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

On the "steerability" of generative adversarial networks

Tutorial on GANs

Tutorial for using Kitti dataset easily

Tutorial covering Open Source tools for Source Separation.

Tutorials on visualizing data using python packages like bokeh, plotly, seaborn and igraph

Notes, Codes, and Tutorials for the Deep Learning Course <which I taught at ChinaHadoop>

Tutorials for deep learning