This respository contains my exploration of the newly released TensorFlow 2.0. TensorFlow team introduced a lot of new and useful changes in this release; automatic mixed precision training, flexible custom training, distributed GPU training, enhanced ops for the high-level Keras API are some of my personal favorites. You can see all of the new changes here.
Apart from the official TensorFlow 2.0 guide and the tutorials, I highly recommend the following resources if you want to learn more about TensorFlow 2.0 (updated on an ad-hoc basis):
- tf.keras for Researchers: Crash Course by Francois Chollet
- TensorFlow 2.0 + Keras Crash Course by Francois Chollet
- Inside TensorFlow: tf.Keras (part 1) by Francois Chollet
- Inside TensorFlow: tf.Keras (part 2) by Francois Chollet
- Introduction to TensorFlow in Python by DataCamp (Instructor: Isaiah Hull)
- TensorFlow in Practice by Coursera (Instructor: Laurence Moroney)
- Ten Important Updates from TensorFlow 2.0 (article by me)
- Hands-On Machine Learning with Scikit-Learn, Keras and Tensor Flow (best-selling book by Aurélien Géron)
- Deep Learning for Computer Vision with Python by Adrian Rosebrock
- Intro to TensorFlow for Deep Learning by Udacity (Instructors: Magnus Hyttsten, Juan Delgado, Paige Bailey)
- Practical Machine Learning with Tensorflow by NPTEL (Instructor: Ashish Tendulkar)
- Hands-On Neural Networks with TensorFlow 2.0 (book by Paolo Galeone)
- TensorFlow: Data and Deployment Specialization by Coursera (Instructor: Laurence Moroney)
- Keras vs. tf.keras: What’s the difference in TensorFlow 2.0? by PyImageSearch