In this video we use our implementation from the last video of naive bayes classifier to classify emails into spam and not spam using the Python programming language. Other words for this: Spam filtering and spam detection using Naive Bayes.

People often ask what courses are great for getting into ML/DL and the two I started with is ML and DL specialization both by Andrew Ng. Below you'll find both affiliate and non-affiliate links if you want to check it out. The pricing for you is the same but a small commission goes back to the channel if you buy it through the affiliate link.
ML Course (affiliate): https://bit.ly/3qq20Sx
DL Specialization (affiliate): https://bit.ly/30npNrw
ML Course (no affiliate): https://bit.ly/3t8JqA9
DL Specialization (no affiliate): https://bit.ly/3t8JqA9

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Today we're going to talk big picture about what Neural Networks are and how they work. Neural Networks, which are computer models that act like neurons in the human brain, are really popular right now - they're being used in everything from self-driving cars and Snapchat filters to even creating original art! As data gets bigger and bigger neural networks will likely play an increasingly important role in helping us make sense of all that data.

Special thanks to Max Deutsch giving us permission to use his Neural Network-written Harry Potter chapter in this episode! Read more about his work here:
https://medium.com/deep-writin....g/harry-potter-writt

Neural Network to create anime characters:
https://arxiv.org/pdf/1708.05509.pdf

Neural Network to great Van Gogh-like art:
https://towardsdatascience.com..../gangogh-creating-ar

Neural Network to create skate decks:
https://github.com/RJT1990/gandecks/

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