The Naive Bayes classifier is a simple classifier that classifies based on probabilities of events. It is the applied commonly to text classification. Though it is a simple algorithm, it performs well in many text classification problems. Other Pros include less training time and less training data. Please join as a member in my channel to get additional benefits like materials in Data Science, live streaming for Members and many more https://www.youtube.com/channel/UCNU_lfiiWBdtULKOw6X0Dig/join Please do subscribe my other channel too https://www.youtube.com/channel/UCjWY5hREA6FFYrthD0rZNIw If you want to Give donation to support my channel, below is the Gpay id GPay: krishnaik06@okicici Connect with me here: Twitter: https://twitter.com/Krishnaik06 Facebook: https://www.facebook.com/krishnaik06 instagram: https://www.instagram.com/krishnaik06
Monet or Picasso? In this episode, we’ll train our own image classifier, using TensorFlow for Poets. Along the way, I’ll introduce Deep Learning, and add context and background on why the classifier works so well. Here are links to learn more, thanks for watching, and have fun! TensorFlow for Poets Codelab: https://goo.gl/QTwZ3v Google’s Udacity class on Deep Learning: https://goo.gl/iRqXsy TensorFlow tutorial: https://goo.gl/0Oz7B5 Google Research blog on Inception: https://goo.gl/CSrfJ1 You can follow me on Twitter at https://twitter.com/random_forests for updates on episodes, and of course – Google Developers. Subscribe to Google Developers: http://goo.gl/mQyv5L – Subscribe to the brand new Firebase Channel: https://goo.gl/9giPHG And here’s our playlist: https://goo.gl/KewA03