A toy complier.
Automatic searching question by speech recognition.
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.
Shadowsocks server with bandwidth limitation.
Some experimental algorithms.
GitHub Pages site.
Bitcoin white paper translation.
Service discovery for Prometheus using devices from Netbox
Prometheus exporter that mines /proc to report on selected processes
The default personal blogging theme for Ghost.
Python API for https://www.spiral.exchange/
i7z without ncurses.
Some articles.
Launch a HTTPS blog platform by docker-compose.
Translate Chinese address to Pinyin.
Minimize code size by removing address parsing.
Yunba performance test.
Slides designed by remarkjs.
Make pretty format for goldendict scan popup.
A simple file server for test.