5 Best Online courses on TensorFlow. Learn TensorFlow Today!

By POOJA BISHT |Email | May 16, 2019 | 7821 Views

Further to my previous article on the best resources on TensorFlow, this article is intended to provide you the necessary details on the best online courses on tensorFlow. 
You can refer to the previous article from here- CLICK

Here is the list of 5 Best courses on TensorFlow that are available Online:

Provided through Coursera the course will make you learn:
  1. the best practices for using TensorFlowlligence, Machine Learning, and De
  2. Building a neural network in TensorFlow
  3. Training a neural network for a computer vision application
  4. Teaches you to use TensorFlow to implement the principles of Machine Learning and Deep Learning to build models to real-world problems.
52926 students have already enrolled for the course. So you can see how widely the course is among the students.

The course requires you to have some prior experience with coding. If you are a software developer and want to learn about using Tensorflow than the course is meant for you.

Right from explaining the basic understanding of  What a machine learning is,  the course will take you through a series of concepts in setting up a supervised learning problem, writing distributed machine learning models that scale in Tensorflow, incorporating the right mix of parameters that yields accurate, generalized models and a detailed conceptual knowledge in Tensorflow. 

30,187 students have already enrolled for the course.

You must have some concepts in Machine Learning, Deep Learning and in Python & Jupyter notebooks before enrolling for this course. The foundational concepts in TensorFlow that are required by you to learn are provided in the course. You will understand through this course:
  1. different types of Deep Architectures, such as Convolutional Networks, Recurrent Networks, and Autoencoders.
  2. Applying TensorFlow for backpropagation
  3. how TensorFlow can be used in curve fitting, regression, classification, and minimization of error functions.
  4. how to apply TensorFlow for backpropagation to tune the weights and biases

You Should have Some knowledge of programming and must have some knowledge of math before starting this course.
The various concepts that are covered in the course are:
  1. TensorFlow Basics
  2. Artificial Neural Networks
  3. Densely Connected Networks
  4. Reinforcement Learning
After this course, you will be able to
  1. Use TensorFlow for solving Unsupervised Learning Problems with AutoEncoders
  2. Use TensorFlow for Time Series Analysis with Recurrent Neural Networks
  3. Build your own Neural Network from Scratch with Python
And many more important skills possessed by any advanced learner in TensorFlow.

Provided by Simplilearn the course covers the main topics like:
  1. Deep Learning with TensorFlow
  2.  Regression example
  3. TensorBoard
  4. Modularity
  5. Keras 
And many more useful concepts of Tensorflow that every learner should know. The course is for anyone who wants to learn TensorFlow.

Source: HOB