torchrec
d2l-en
torchrec | d2l-en | |
---|---|---|
1 | 6 | |
1,737 | 21,922 | |
1.8% | 2.3% | |
9.8 | 8.5 | |
4 days ago | 11 days ago | |
Python | Python | |
BSD 3-clause "New" or "Revised" License | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
torchrec
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Pytorch Introduces ‘TorchRec’: A Python-based PyTorch Domain Library For Recommendation Systems (RecSys)
TorchRec is a new PyTorch domain library for Recommendation Systems. This library includes standard sparsity and parallelism primitives, allowing researchers to create and implement cutting-edge customization models. CONTINUE READING
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?
Federated-Recommendation-Neural-Collaborative-Filtering - Federated Neural Collaborative Filtering (FedNCF). Neural Collaborative Filtering utilizes the flexibility, complexity, and non-linearity of Neural Network to build a recommender system. Aim to federate this recommendation system.
Pytorch-UNet - PyTorch implementation of the U-Net for image semantic segmentation with high quality images
federeco - implementation of federated neural collaborative filtering algorithm
DeepADoTS - Repository of the paper "A Systematic Evaluation of Deep Anomaly Detection Methods for Time Series".
warp-drive - Extremely Fast End-to-End Deep Multi-Agent Reinforcement Learning Framework on a GPU (JMLR 2022)
TF-Watcher - Monitor your ML jobs on mobile devices📱, especially for Google Colab / Kaggle
NVTabular - NVTabular is a feature engineering and preprocessing library for tabular data designed to quickly and easily manipulate terabyte scale datasets used to train deep learning based recommender systems.
99-ML-Learning-Projects - A list of 99 machine learning projects for anyone interested to learn from coding and building projects
LLMRec - [WSDM'2024 Oral] "LLMRec: Large Language Models with Graph Augmentation for Recommendation"
imbalanced-regression - [ICML 2021, Long Talk] Delving into Deep Imbalanced Regression
NewsMTSC - Target-dependent sentiment classification in news articles reporting on political events. Includes a high-quality data set of over 11k sentences and a state-of-the-art classification model.
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.