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Welcome to the Llama Cookbook! This is your go to guide for Building with Llama: Getting started with Inference, Fine-Tuning, RAG. We also show you how to solve end to end problems using Llama model family and using them on various provider services

TranslatedAlgorithm Patterns — the most scientific way to practice, the fastest path to an offer. You deserve it~ Algorithm templates, the most scientific way to practice problems, the fastest path to practice problems, you deserve it~

TranslatedA programmer who loves cooking and is determined to use animations to explain algorithms in plain, easy-to-understand terms. My interview website: www.chengxuchu.com

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.