symao's starred repositories
handson-ml2
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
handson-ml
⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 instead.
deep-learning-with-python-notebooks
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
LaTeX-Workshop
Boost LaTeX typesetting efficiency with preview, compile, autocomplete, colorize, and more.
machine-learning-systems-design
A booklet on machine learning systems design with exercises. NOT the repo for the book "Designing Machine Learning Systems"
awesome-self-supervised-learning
A curated list of awesome self-supervised methods
sklearn-doc-zh
:book: [译] scikit-learn（sklearn） 中文文档
zhihu
This repo contains the source code in my personal column (https://zhuanlan.zhihu.com/zhaoyeyu), implemented using Python 3.6. Including Natural Language Processing and Computer Vision projects, such as text generation, machine translation, deep convolution GAN and other actual combat code.
Automatic_Speech_Recognition
End-to-end Automatic Speech Recognition for Madarian and English in Tensorflow
pytorch-kaldi
pytorch-kaldi is a project for developing state-of-the-art DNN/RNN hybrid speech recognition systems. The DNN part is managed by pytorch, while feature extraction, label computation, and decoding are performed with the kaldi toolkit.
keras-preprocessing
Utilities for working with image data, text data, and sequence data.
keras-radam
RAdam implemented in Keras & TensorFlow
label-refinery
Label Refinery: Improving ImageNet Classification through Label Progression
universal_differential_equations
Repository for the Universal Differential Equations for Scientific Machine Learning paper, describing a computational basis for high performance SciML
hypertunity
A toolset for black-box hyperparameter optimisation.
Tensorflow-2.0-Quick-Start-Guide
Tensorflow 2.0 Quick Start Guide, published by Packt
noisy_label_understanding_utilizing
ICML 2019: Understanding and Utilizing Deep Neural Networks Trained with Noisy Labels
wsss-analysis
A Comprehensive Analysis of Weakly-Supervised Semantic Segmentation in Different Image Domains (IJCV submission)
What-s-New-in-TensorFlow-2.0
What's New in TensorFlow 2.0, Published by Packt
hoDMD-experiments
EigenSent: Spectral sentence embeddings using higher-order Dynamic Mode Decomposition
tensorflow-template
A template for Tensorflow 2.0 + Keras projects