TensorFlow is one of the most powerful frameworks for Machine Learning. It was created by Google and used by companies like Airbnb, Spotify, and Google. So if you are looking for the best resources to learn TensorFlow, this article is for you. This article will take you through some of the best resources to learn TensorFlow for Machine Learning.
Here’s How to Learn TensorFlow for Machine Learning
Below are some of the best resources you can follow to learn TensorFlow for Machine Learning.
Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning
Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning is a course offered by DeepLearning.AI on Coursera. It will teach you the best practices for using TensorFlow for Machine Learning. Below are some of the skills you will learn from this course:
- the best practices for using TensorFlow
- building a neural network architecture using TensorFlow
- training a neural network for computer vision
- using convolutions to improve neural network
You can find more information about signing up for this course here.
Machine Learning with TensorFlow
Machine Learning with TensorFlow is a comprehensive guide on building machine learning models using TensorFlow and the Python programming language. Here you will learn to use TensorFlow for solving real-world problems like sentiment analysis, text classification, and image recognition. Below are some of the skills you will learn from this book:
- implementation of Machine Learning with TensorFlow
- choosing the best machine learning algorithm
- visualizing algorithms with TensorBoard
- running your machine learning models in Docker
You can find this book here.
Summary
So these are some of the best resources you can follow for learning TensorFlow for Machine Learning. TensorFlow is one of the most powerful frameworks for Machine Learning. I hope you liked this article on how to learn TensorFlow for Machine Learning. Feel free to ask valuable questions in the comments section below.