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2021-cs109b

51bitquant

51bitquant Python数字货币量化交易视频 CCXT框架 爬取交易所数据 比特币量化交易 交易机器人51bitquant tradingbot cryptocurrency quantitative trading btc trading

awesome-incremental-learning

Awesome Incremental Learning

banditlib

Library of contextual bandits algorithms

batch-active-preference-based-learning

Companion code to CoRL 2018 paper: E Bıyık, D Sadigh. "Batch Active Preference-Based Learning of Reward Functions". Conference on Robot Learning (CoRL), Zurich, Switzerland, Oct. 2018.

biobootcamp

bitpredict

Machine learning for high frequency bitcoin price prediction

chicago-course-work

Work for courses taken at University of Chicago

course_codes

VNPY 2020 Python数字货币量化交易视频教程课程代码和资料

covid19_critically_ill

Trained model and inference code for early triage of critically-ill COVID-19 patients.

ctci-6th-edition-python

Cracking the Coding Interview 6th Ed. Python Solutions

deepbeerinventory-rl

The code for the SRDQN algorithm to train an agent for the beer game problem

ebay

Replication files for "Optimal Bargaining on eBay"

famous_quotations

Just for fun and inspirations :)

fastbook

The fastai book, published as Jupyter Notebooks

gym-mo

Simulation environments for Multi-Objective Reinforcement Learning (MORL)

highwayenv

A minimalist environment for decision-making in autonomous driving

howtrader

howtrader: how to be a quant trader, forked from vnpy with easy installation and deployment

lstm-neural-network-for-time-series-prediction

LSTM built using Keras Python package to predict time series steps and sequences. Includes sin wave and stock market data

minihack

MiniHack the Planet: A Sandbox for Open-Ended Reinforcement Learning Research

misc

Miscellaneous collections of curiosity

ml-nlp

此项目是机器学习(Machine Learning)、深度学习(Deep Learning)、NLP面试中常考到的知识点和代码实现，也是作为一个算法工程师必会的理论基础知识。

mxnetworkshophongkong

MXNet Workshop in Hong Kong 2018

nus-slides-latex-template

A latex template for the convenience of NUS students to prepare for their presentation slides.

nushpc

pydata-book

Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media

pythondatasciencehandbook

Python Data Science Handbook: full text in Jupyter Notebooks

robotics

screening-decision-cm

stockpredictionai

In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.