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TranslatedDeep Learning 500 Questions: in question-and-answer form, it covers hot topics in commonly used probability, linear algebra, machine learning, deep learning, computer vision and more, to help myself and readers who need it. The book is divided into 18 chapters and has more than 500,000 characters. Due to limited ability, readers are kindly asked to criticize and correct any improper parts of the book. To be continued............ If you are interested in cooperating, contact [email protected]. All rights reserved, infringement will be prosecuted. Tan 2018.06

30 days of JavaScript programming challenge is a step-by-step guide to learn JavaScript programming language in 30 days. This challenge may take more than 100 days, please just follow your own pace. These videos may help too: https://www.youtube.com/channel/UC7PNRuno1rzYPb1xLa4yktw

  • 30daysofjavascript
  • javascript-for-everyone
  • css
  • html

Source for remoteintech.company — a community-maintained directory of remote-friendly tech companies

  • remote
  • jobsearch
  • jobs-search
  • remote-work

30 Days of React challenge is a step by step guide to learn React in 30 days. These videos may help too: https://www.youtube.com/channel/UC7PNRuno1rzYPb1xLa4yktw

  • challenge
  • javascript
  • js
  • react

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.