pytorch-summary
d2l-en
| pytorch-summary | d2l-en | |
|---|---|---|
| 2 | 6 | |
| 3,957 | 21,704 | |
| - | 3.5% | |
| 0.0 | 8.5 | |
| about 2 months ago | 9 days ago | |
| Python | Python | |
| MIT License | GNU General Public License v3.0 or later |
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pytorch-summary
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Conv3D
could try this package, pytorch-summary package if you havent
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Why is CUDA running out of memory?
This could be because of session thats is running in background which you need to terminate and refresh.Or it might be due to large nn model so maybe try changing the number of layers and neurons in the model.This summary library might help you check the size of your nn model
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?
livelossplot - Live training loss plot in Jupyter Notebook for Keras, PyTorch and others
Pytorch-UNet - PyTorch implementation of the U-Net for image semantic segmentation with high quality images
horovod - Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.
DeepADoTS - Repository of the paper "A Systematic Evaluation of Deep Anomaly Detection Methods for Time Series".
wandb - 🔥 A tool for visualizing and tracking your machine learning experiments. This repo contains the CLI and Python API.
TF-Watcher - Monitor your ML jobs on mobile devices📱, especially for Google Colab / Kaggle
netron - Visualizer for neural network, deep learning and machine learning models
99-ML-Learning-Projects - A list of 99 machine learning projects for anyone interested to learn from coding and building projects
pytorch-model-details - Package to visualize all the layer parameters of a deep learning model.
imbalanced-regression - [ICML 2021, Long Talk] Delving into Deep Imbalanced Regression
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.
einops - Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)