A Complete Guide on TensorFlow 2.0 using Keras API
Build Amazing Applications of Deep Learning and Artificial Intelligence in TensorFlow 2.0
Created by Hadelin de Ponteves, Kirill Eremenko, SuperDataScience Team, Luka Anicin | 13 hours on-demand video course
Welcome to Tensorflow 2.0! TensorFlow 2.0 has just been released, and it introduced many features that simplify the model development and maintenance processes. From the educational side, it boosts people’s understanding by simplifying many complex concepts. From the industry point of view, models are much easier to understand, maintain, and develop.
What you’ll learn
- How to use Tensorflow 2.0 in Data Science
- Important differences between Tensorflow 1.x and Tensorflow 2.0
- How to implement Artificial Neural Networks in Tensorflow 2.0
- How to implement Convolutional Neural Networks in Tensorflow 2.0
- How to implement Recurrent Neural Networks in Tensorflow 2.0
- How to build your own Transfer Learning application in Tensorflow 2.0
- How to build a stock market trading bot using Reinforcement Learning (Deep-Q Network)
- How to build Machine Learning Pipeline in Tensorflow 2.0
- How to conduct Data Validation and Dataset Preprocessing using TensorFlow Data Validation and TensorFlow Transform.
- Putting a TensorFlow 2.0 model into production
- How to create a Fashion API with Flask and TensorFlow 2.0
- How to serve a TensorFlow model with RESTful API
Recommended Course
Complete Machine Learning and Data Science: Zero to Mastery
Complete Tensorflow 2 and Keras Deep Learning Bootcamp
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