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TranslatedFocus on fundamentals and build a high-quality front-end blog; author of the WeChat official account [前端工匠] (Front-end Craftsman)

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.

TranslatedA beginner's bible for AI that doesn't play at being obscure or cater to a niche few, easy to grasp for everyone from students to engineers. It covers neural networks to large models, top-level design to micro-level principles, and engineering implementation to algorithm fundamentals. After studying it, you will thoroughly understand why the seemingly unremarkable ability of next-token prediction can change the world, and you will also discover that AI is not as mysterious or as unattainable as imagined. Let's just beat it !