Jiaxi Tang's starred repositories
revisit_adv_rec
A PyTorch implementation for the Recsys 2020 paper: Revisiting Adversarially Learned Injection Attacks Against Recommender Systems
roformer-v2
RoFormer升级版
learning-notes
Notes on books I read, talks I watch, articles I study, and papers I love
tf-quant-finance
High-performance TensorFlow library for quantitative finance.
partial-encoder-decoder
An encoder-decoder framework for learning from incomplete data
Linear-Algebra-With-Python
Lecture Notes for Linear Algebra Featuring Python. This series of lecture notes will walk you through all the must-know concepts that set the foundation of data science or advanced quantitative skillsets. Suitable for statistician/econometrician, quantitative analysts, data scientists and etc. to quickly refresh the linear algebra with the assistance of Python computation and visualization.
uncertainty-baselines
High-quality implementations of standard and SOTA methods on a variety of tasks.
qlib
Qlib is an AI-oriented quantitative investment platform that aims to realize the potential, empower research, and create value using AI technologies in quantitative investment, from exploring ideas to implementing productions. Qlib supports diverse machine learning modeling paradigms. including supervised learning, market dynamics modeling, and RL.
recommenders
TensorFlow Recommenders is a library for building recommender system models using TensorFlow.
Hands-On-Machine-Learning-with-CPP
Hands-On Machine Learning with C++, published by Packt
cvx_short_course
Materials for a short course on convex optimization.
MML-Companion
This is a companion to the ‘Mathematical Foundations’ section of the book, Mathematics for Machine Learning by Marc Deisenroth, Aldo Faisal and Cheng Ong, written in python for Jupyter Notebook.
ml-design-patterns
Source code accompanying O'Reilly book: Machine Learning Design Patterns
i-hate-regex
The code for iHateregex.io 😈 - The Regex Cheat Sheet
fast-soft-sort
Fast Differentiable Sorting and Ranking
DeepCTR-Torch
【PyTorch】Easy-to-use,Modular and Extendible package of deep-learning based CTR models.
sparse_attention
Examples of using sparse attention, as in "Generating Long Sequences with Sparse Transformers"