d2l-en
imbalanced-regression
| d2l-en | imbalanced-regression | |
|---|---|---|
| 6 | 1 | |
| 21,759 | 757 | |
| 1.6% | - | |
| 8.5 | 1.8 | |
| 18 days ago | about 2 years ago | |
| Python | Python | |
| GNU General Public License v3.0 or later | MIT License |
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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.
imbalanced-regression
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[R] Strategies and Tactics for Regression on Imbalanced Data
Code (+ dataset + models): https://github.com/YyzHarry/imbalanced-regression
What are some alternatives?
Pytorch-UNet - PyTorch implementation of the U-Net for image semantic segmentation with high quality images
autogluon - Fast and Accurate ML in 3 Lines of Code
DeepADoTS - Repository of the paper "A Systematic Evaluation of Deep Anomaly Detection Methods for Time Series".
pneumonia_detection - Pneumonia Detection using machine learning - with PyTorch
TF-Watcher - Monitor your ML jobs on mobile devices📱, especially for Google Colab / Kaggle
healthsea - Healthsea is a spaCy pipeline for analyzing user reviews of supplementary products for their effects on health.
99-ML-Learning-Projects - A list of 99 machine learning projects for anyone interested to learn from coding and building projects
ludwig - Low-code framework for building custom LLMs, neural networks, and other AI models
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.
multi-domain-imbalance - [ECCV 2022] Multi-Domain Long-Tailed Recognition, Imbalanced Domain Generalization, and Beyond
einops - Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)
learning-topology-synthetic-data - Tensorflow implementation of Learning Topology from Synthetic Data for Unsupervised Depth Completion (RAL 2021 & ICRA 2021)