TOP 10 free resources to learn TensorFlow in 2020 (Updated)

Complete Guide to TensorFlow for Deep Learning with Python

TensorFlow is an open-source programming library for machine learning over a scope of tasks. It is a system for building and training neural networks to identify and decipher patterns and correlations , practically equivalent to (yet not the same as) human learning and thinking. It is utilized for both research and creation at Google.

TensorFlow was produced by the Google Mind group for interior Google utilize. It was discharged under the Apache 2.0 open source permit on November 9, 2015.

TensorFlow is Google Brain’s second era system . Version 1.0.0 was discharged on February 11, 2017. While the reference execution keeps running on single gadgets, TensorFlow can run on multiple CPUs and GPUs (with discretionary CUDA augmentations for universally useful figuring on illustrations handling units).TensorFlow is accessible on 64-bit Linux, macOS, Windows, and  mobile computing platforms including Android and iOS.

 

“Try to improve your codes so as to extract maximum performance out of TensorFlow”

 

 

 

TensorFlow computations are expressed as stateful dataflow diagrams. The name TensorFlow gets from the operations that such neural networks perform on multidimensional data arrays . These arrays are referred to as “tensors”.

 

 

Advanced ML with TensorFlow on Google Cloud Platform Specialization 

Description: This 5-course specialization focuses on advanced machine learning topics using Google Cloud Platform where you will get hands-on experience optimizing, deploying, and scaling production ML models of various types in hands-on labs. This specialization picks up where “Machine Learning on GCP” left off and teaches you how to build scalable, accurate, and production-ready models for structured data, image data, time-series, and natural language text.

It ends with a course on building recommendation systems. Topics introduced in earlier courses are referenced in later courses, so it is recommended that you take the courses in exactly this order.

 

Course Link here

 

 

 

 

 Deep Learning With TensorFlow

Description: TensorFlow is one of the best libraries to implement deep learning. TensorFlow is a software library for numerical computation of mathematical expressional, using data flow graphs. Nodes in the graph represent mathematical operations, while the edges represent the multidimensional data arrays (tensors) that flow between them. It was created by Google and tailored for Machine Learning. In fact, it is being widely used to develop solutions with Deep Learning.

In this TensorFlow course, you will learn the basic concepts of TensorFlow, the main functions, operations and the execution pipeline. Starting with a simple “Hello Word” example, throughout the course you will be able to see how TensorFlow can be used in curve fitting, regression, classification and minimization of error functions.

 

Course Link here 

 

 

 

 TensorFlow and Deep Learning – without a PhD.

 

 

 

 

 

 Introduction to TensorFlow For AI, ML and Deep Learning

Description: If you are a software developer who wants to build scalable AI-powered algorithms, you need to understand how to use the tools to build them. This course is part of the upcoming Machine Learning in Tensorflow Specialization and will teach you best practices for using TensorFlow, a popular open-source framework for machine learning.

The Machine Learning course and Deep Learning Specialization from Andrew Ng teach the most important and foundational principles of Machine Learning and Deep Learning. This new deeplearning.ai TensorFlow Specialization teaches you how to use TensorFlow to implement those principles so that you can start building and applying scalable models to real-world problems. To develop a deeper understanding of how neural networks work, we recommend that you take the Deep Learning Specialization.

 

Course Link here 

 

 

 

 Intro to TensorFlow for Deep Learning by TensorFlow

Description: Learn how to build deep learning applications with TensorFlow. This course was developed by the TensorFlow team and Udacity as a practical approach to deep learning for software developers. You’ll get hands-on experience building your own state-of-the-art image classifiers and other deep learning models. You’ll also use your TensorFlow models in the real world on mobile devices, in the cloud, and in browsers.

Finally, you’ll use advanced techniques and algorithms to work with large datasets. By the end of this course, you’ll have all the skills necessary to start creating your own AI applications.

Course Link here

 

 

 Introduction to TensorFlow Lite by TensorFlow Lite

Description: Learn how to deploy deep learning models on mobile and embedded devices with TensorFlow Lite. This course was developed by the TensorFlow team and Udacity as a practical approach to model deployment for software developers.

You’ll get hands-on experience with the TensorFlow Lite framework as you deploy deep learning models on Android, iOS, and even an embedded Linux platform. By the end of this course, you’ll have all the skills necessary to start deploying your own deep learning models into your apps.

Course Link here

 

 

 

 

 

Machine Learning with TensorFlow on Google Cloud Platform Specialization

Description: This course “Machine Learning with TensorFlow on Google Cloud Platform Specialization” is offered by Google Cloud in Coursera. In this course, one can learn the basics of machine learning and the problems it can solve. One will also learn how to write distributed machine learning models that scale in Tensorflow. It also helps the student in scaling out the training of those models by offer high-performance predictions and other such.

 

Course Link here 

 

 

Natural Language Processing in TensorFlow

Description: If you are a software developer who wants to build scalable AI-powered algorithms, you need to understand how to use the tools to build them. This Specialization will teach you best practices for using TensorFlow, a popular open-source framework for machine learning. In Course 3 of the deeplearning.ai TensorFlow Specialization, you will build natural language processing systems using TensorFlow. You will learn to process text, including tokenizing and representing sentences as vectors, so that they can be input to a neural network. You’ll also learn to apply RNNs, GRUs, and LSTMs in TensorFlow.

Finally, you’ll get to train an LSTM on existing text to create original poetry! The Machine Learning course and Deep Learning Specialization from Andrew Ng teach the most important and foundational principles of Machine Learning and Deep Learning. This new deeplearning.ai TensorFlow Specialization teaches you how to use TensorFlow to implement those principles so that you can start building and applying scalable models to real-world problems. To develop a deeper understanding of how neural networks work, we recommend that you take the Deep Learning Specialization.

Course Link here

 

 

 

 

Further interest related Tutorials/Documents can be found below

 

 

Official Documentation

Course Link here

 

TensorFlow Tutorial For Beginners

Course Link here.

 

TensorFlow Tutorial

Course Link here.

 

Introduction to Deep Learning with TensorFlow

Course Link here.

 

TensorFlow Tutorial – Deep Learning Using TensorFlow

Course Link here.

Python TensorFlow Tutorial – Build a Neural Network

Course Link here

 

 

TensorFlow Tutorials

Course Link here 

 

 

 

Related:

https://favouriteblog.com/the-ultimate-list-of-tensorflow-resources-books-tutorials/

https://favouriteblog.com/learn-tensorflow-and-deep-learning-without-a-phd/

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