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.
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Code examples that accompany various MDN DOM and Web API documentation pages
- matchmedia
- demo
- drag-drop
- dom-manipulation
Various recipes for testing common scenarios with Cypress
- testing
- examples
- recipes
- unit-testing
I created this repository to keep my learning, notes, and code in one place for various tools in DevOps. Now, it's helping thousands of learners, practitioners, and professionals every day in their DevOps journey.
- docker
- kubernetes
- yaml
- devops
Learn to code securely while having fun through our popular open source in-editor experience, designed for developers, students, and anyone curious about security. Get started for free in under 2 minutes, playing right from your browser.
- code-security
- ai
- ai-security
- coding-training
Open source eBook for nodejs - written w/ markdown, outputs to various formats (pdf, mobi, epub, html, etc)
Interactive web playground for various Computational Geometry algorithms and topics using p5.js