A collection of various deep learning architectures, models, and tips
Debugging, monitoring and visualization for Python Machine Learning and Data Science
Reference models and tools for Cloud TPUs.
Implementations of a number of generative models in Tensorflow 2. GAN, VAE, Seq2Seq, VAEGAN, GAIA, Spectrogram Inversion. Everything is self contained in a jupyter notebook for easy export to colab.
Adaptive Experimentation Platform
tensorflow2中文教程，持续更新(当前版本:tensorflow2.0)，tag: tensorflow 2.0 tutorials
Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.
A complete ML study path, focused on TensorFlow and Scikit-Learn
有趣的Python爬虫和Python数据分析小项目(Some interesting Python crawlers and data analysis projects)
One has no future if he couldn’t teach himself.