torch-metrics
d2l-en
| torch-metrics | d2l-en | |
|---|---|---|
| 2 | 6 | |
| 109 | 21,704 | |
| - | 1.3% | |
| 1.8 | 8.5 | |
| about 3 years ago | 10 days ago | |
| Python | Python | |
| MIT License | GNU General Public License v3.0 or later |
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torch-metrics
- Torch Metrics Library
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[P] Contributions needed for PyTorch metrics library
Hi all I've created a metrics library for PyTorch here but will need lots of contributions to make it as user friendly as possible. Feature requests/ contributions are welcome :) Feel free to use it in your projects if you find it useful. Thanks.
d2l-en
- which book to chose for deep learning :lan Goodfellow or francois chollet
- d2l-en: Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 400 universities from 60 countries including Stanford, MIT, Harvard, and Cambridge.
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How to pre-train BERT on different objective tasks using HuggingFace
There might is bert library for pre-train bert model in huggingface, But I suggestion that you train bert model in native pytorch to understand detail, Limu's course is recommended for you
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The Transformer in Machine Translation
GitHub's article on Dive into Deep Learning
- D2l-En
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I created a way to learn machine learning through Jupyter
There are actually some online books and courses built on Jupyter Notebook ([Dive to Deep Learning Book](https://github.com/d2l-ai/d2l-en) for example). However yours is more detail and could really helps beginners.
What are some alternatives?
ignite - High-level library to help with training and evaluating neural networks in PyTorch flexibly and transparently.
Pytorch-UNet - PyTorch implementation of the U-Net for image semantic segmentation with high quality images
Robo-Semantic-Segmentation - Just a simple semantic segmentation library that I developed to speed up the image segmentation pipeline
DeepADoTS - Repository of the paper "A Systematic Evaluation of Deep Anomaly Detection Methods for Time Series".
ALAE - [CVPR2020] Adversarial Latent Autoencoders
TF-Watcher - Monitor your ML jobs on mobile devices📱, especially for Google Colab / Kaggle
PyTorch-VAE - A Collection of Variational Autoencoders (VAE) in PyTorch.
99-ML-Learning-Projects - A list of 99 machine learning projects for anyone interested to learn from coding and building projects
onemetric - One Metrics Library to Rule Them All!
imbalanced-regression - [ICML 2021, Long Talk] Delving into Deep Imbalanced Regression
datasets - 🤗 The largest hub of ready-to-use datasets for ML models with fast, easy-to-use and efficient data manipulation tools
petastorm - Petastorm library enables single machine or distributed training and evaluation of deep learning models from datasets in Apache Parquet format. It supports ML frameworks such as Tensorflow, Pytorch, and PySpark and can be used from pure Python code.