Repository Index

TranslatedHan Xiankai's (韩先凯) Life Advancement Guide: a bilingual Chinese-English lifelong learning guide for the AI era, covering AI, learning, entrepreneurship, wealth, love, and life

• chinese
• tutorial
• english-learning
• ai-literacy

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.

A K6 Multi Scenario template applying some best practices along some examples