lambda-packs
d2l-en
lambda-packs | d2l-en | |
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1 | 6 | |
1,106 | 21,759 | |
- | 1.6% | |
4.0 | 8.5 | |
6 months ago | 16 days ago | |
Python | Python | |
MIT License | GNU General Public License v3.0 or later |
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lambda-packs
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Using TensorFlow and the Serverless Framework for deep learning and image recognition
As a hobby, I port a lot of libraries to make the serverless friendly. You can look at them here. They all have an MIT license, so feel free to modify and use them for your project.
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?
equilib - 🌎→🗾Equirectangular (360/panoramic) image processing library for Python with minimal dependencies only using Numpy and PyTorch
Pytorch-UNet - PyTorch implementation of the U-Net for image semantic segmentation with high quality images
thinc - 🔮 A refreshing functional take on deep learning, compatible with your favorite libraries
DeepADoTS - Repository of the paper "A Systematic Evaluation of Deep Anomaly Detection Methods for Time Series".
data-science-ipython-notebooks - Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
TF-Watcher - Monitor your ML jobs on mobile devices📱, especially for Google Colab / Kaggle
mars - Mars is a tensor-based unified framework for large-scale data computation which scales numpy, pandas, scikit-learn and Python functions.
99-ML-Learning-Projects - A list of 99 machine learning projects for anyone interested to learn from coding and building projects
einops - Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)
imbalanced-regression - [ICML 2021, Long Talk] Delving into Deep Imbalanced Regression
Photomosaic-Creator - This script allows you to create a photomosaic from a set of images.
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.