Jingyu Zhou's repositories
flow-examples
An independent Actor programming library, i.e., flow language, from FoundationDB project with examples.
foundationdb
FoundationDB - the open source, distributed, transactional key-value store
alpaca.cpp
Locally run an Instruction-Tuned Chat-Style LLM
DeepLearning-NLP
Introduction to Deep Learning for Natural Language Processing
Distributional-Signatures
Few-shot Text Classification with Distributional Signatures
fdb-build-support
FoundationDB build and development resources
fdb-joshua
FoundationDB Correctness service
libcircllhist
A C implementation of OpenHistogram log-linear histograms
shadowsocks
backup of https://github.com/shadowsocks/shadowsocks
shadowsocksr
Python port of ShadowsocksR
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.