recommenders
d2l-en
| recommenders | d2l-en | |
|---|---|---|
| 1 | 6 | |
| 1,763 | 21,922 | |
| 1.3% | 2.3% | |
| 4.7 | 8.5 | |
| 8 days ago | 13 days ago | |
| Python | Python | |
| Apache License 2.0 | 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.
recommenders
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How to implement MultipleNegativesRankingLoss in TF?
I have found a similar approach here https://github.com/tensorflow/recommenders/blob/main/tensorflow_recommenders/tasks/retrieval.py
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?
rexmex - A general purpose recommender metrics library for fair evaluation.
Pytorch-UNet - PyTorch implementation of the U-Net for image semantic segmentation with high quality images
Surprise - A Python scikit for building and analyzing recommender systems
DeepADoTS - Repository of the paper "A Systematic Evaluation of Deep Anomaly Detection Methods for Time Series".
riscv-newop - A RISC-V new instruction discovery tool [Work in Progress]
TF-Watcher - Monitor your ML jobs on mobile devices📱, especially for Google Colab / Kaggle
LightFM - A Python implementation of LightFM, a hybrid recommendation algorithm.
99-ML-Learning-Projects - A list of 99 machine learning projects for anyone interested to learn from coding and building projects
TensorRec - A TensorFlow recommendation algorithm and framework in Python.
imbalanced-regression - [ICML 2021, Long Talk] Delving into Deep Imbalanced Regression
RecBole - A unified, comprehensive and efficient recommendation library
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.