BryceMeng
There is only one heroism in the world: to see the world as it is and to love it
NYITVancouver
Pinned Repositories
AsyncNMultithread
Awesome-Quant-Machine-Learning-Trading
Quant/Algorithm trading resources with an emphasis on Machine Learning
best-of-ml-python
🏆 A ranked list of awesome machine learning python libraries. Updated weekly.
brycemeng.github.io
personal website
cpp_thread_pool
A c++ thread pool library for class member method
dominant_contract_switch
Analyze contract switching times in China's commodity markets
mlfinlab
Package based on the work of Dr Marcos Lopez de Prado regarding his research with respect to Advances in Financial Machine Learning
mlfinlab_research_bryce
spam-detection-machine-learning
VnpyStudy
Some code was written while learning the VNPY framework
BryceMeng's Repositories
BryceMeng/mlfinlab
Package based on the work of Dr Marcos Lopez de Prado regarding his research with respect to Advances in Financial Machine Learning
BryceMeng/mlfinlab_research_bryce
BryceMeng/VnpyStudy
Some code was written while learning the VNPY framework
BryceMeng/dominant_contract_switch
Analyze contract switching times in China's commodity markets
BryceMeng/brycemeng.github.io
personal website
BryceMeng/cpp_thread_pool
A c++ thread pool library for class member method
BryceMeng/AsyncNMultithread
BryceMeng/Awesome-Quant-Machine-Learning-Trading
Quant/Algorithm trading resources with an emphasis on Machine Learning
BryceMeng/best-of-ml-python
🏆 A ranked list of awesome machine learning python libraries. Updated weekly.
BryceMeng/concurrentqueue
A fast multi-producer, multi-consumer lock-free concurrent queue for C++11
BryceMeng/FinRL-Library
A Deep Reinforcement Learning Library for Automated Trading in Quantitative Finance. NeurIPS 2020.
BryceMeng/spam-detection-machine-learning
BryceMeng/malware-detection-machine-learning
malware detection using machine learning
BryceMeng/nanoGPT
The simplest, fastest repository for training/finetuning medium-sized GPTs.
BryceMeng/stl_perf
BryceMeng/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.
BryceMeng/stockstats
Supply a wrapper ``StockDataFrame`` based on the ``pandas.DataFrame`` with inline stock statistics/indicators support.