📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.

This is the notes of the way of machine learning study. You may find something useful in it.

本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为PyTorch实现。

AI and Machine Learning with Kubeflow, Amazon EKS, and SageMaker

Easy-to-use,Modular and Extendible package of deep-learning based CTR models .

Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.

Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.

本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为TensorFlow 2.0实现，项目已得到李沐老师的认可

Python Data Science Handbook: full text in Jupyter Notebooks

Tensorflow2.0 🍎🍊 is delicious, just eat it! 😋😋

Here are the models listed in CTR. Example: FM、DeepFM、xDeepFM etc.

This project reproduces the book Dive Into Deep Learning (https://d2l.ai/), adapting the code from MXNet into PyTorch.

Useful and handy Jupyter Notebooks for Analysis

Classic papers and resources on recommendation

Tensorflow implementation of DeepFM for CTR prediction.