Best Tensorflow Courses [2020]

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TensorFlow is an open-source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API. TensorFlow was originally developed by researchers and engineers working on the Google Brain Team within Google's Machine Intelligence research organization to conduct machine learning and deep neural networks research, but the system is general enough to be applicable in a wide variety of other domains as well.

It is used by major companies all over the world, including Airbnb, eBay, Dropbox, Snapchat, Twitter, Uber, SAP, Qualcomm, IBM, Intel, and of course, Google!

Tensorflow is the world's most popular library for deep learning, and it's built by Google, whose parent Alphabet recently became the most cash-rich company in the world (just a few days before I wrote this). It is the library of choice for many companies doing AI and machine learning.

Thus, considering the fact of how widespread and popular, this library is, you should certainly learn TensorFlow. And to facilitate your learning, we have curated a list of Best Tensorflow Courses that you must take to get yourself acquainted with the skill.

1. Total TensorFlow Guide: Deep Learning with Python Course

2. TensorFlow: Getting Started

3. Tensorflow 2.0: Deep Learning and Artificial Intelligence

4. Understanding the Foundations of TensorFlow

5. Complete Tensorflow 2 and Keras Deep Learning Bootcamp

1. Total TensorFlow Guide: Deep Learning with Python Course

Learn how to use Google's Deep Learning Framework - TensorFlow with Python! Solve problems with cutting edge techniques!

Course rating: 4.4 out of 5.0 ( 14,661 Ratings total)

In this course, you will :

• Understand how Neural Networks Work.
• Build your own Neural Network from Scratch with Python.
• Use TensorFlow for Classification and Regression Tasks.
• Use TensorFlow for Image Classification with Convolutional Neural Networks.
• Use TensorFlow for Time Series Analysis with Recurrent Neural Networks.
• Use TensorFlow for solving Unsupervised Learning Problems with AutoEncoders.
• Learn how to conduct Reinforcement Learning with OpenAI Gym.
• Create Generative Adversarial Networks with TensorFlow.
• Become a Deep Learning Guru!.
• This course will guide you through how to use Google's TensorFlow framework to create artificial neural networks for deep learning!
• This course aims to give you an easy to understand guide to the complexities of Google's TensorFlow framework in a way that is easy to understand.

You can take Total TensorFlow Guide: Deep Learning with Python Course Certificate Course on Udemy.

2. TensorFlow: Getting Started

This course shows you how to install and use TensorFlow, a leading machine learning library from Google. You'll see how TensorFlow can create a range of machine learning models, from simple linear regression to complex deep neural networks.

Course rating: 4.0 out of 5.0 ( 198 Ratings total)

In this course, you will :

• You'll see how TensorFlow easily addresses these concerns by learning TensorFlow from the bottom up.
• First, you'll be introduced to the installation process, building simple and advanced models, and utilizing additional libraries that make development even easier.
• Along the way, you'll learn how the unique architecture in TensorFlow lets you perform your computing on systems as small as a Raspberry Pi, and as large as a data farm.
• Finally, you'll explore using TensorFlow with neural networks in general, and specifically with powerful deep neural networks.
• By the end of this course, you'll have a solid foundation on using TensorFlow, and know to apply TensorFlow to create your machine learning solutions.

You can take TensorFlow: Getting Started Certificate Course on Pluralsight.

3. Tensorflow 2.0: Deep Learning and Artificial Intelligence

Neural Networks for Computer Vision, Time Series Forecasting, NLP, GANs, Reinforcement Learning, and More!

Course rating: 4.6 out of 5.0 ( 2,756 Ratings total)

In this course, you will :

• Artificial Neural Networks (ANNs) / Deep Neural Networks (DNNs).
• Predict Stock Returns.
• Time Series Forecasting.
• Computer Vision.
• How to build a Deep Reinforcement Learning Stock Trading Bot.
• GANs (Generative Adversarial Networks).
• Recommender Systems.
• Image Recognition.
• Convolutional Neural Networks (CNNs).
• Recurrent Neural Networks (RNNs).
• Use Tensorflow Serving to serve your model using a RESTful API.
• Use Tensorflow Lite to export your model for mobile (Android, iOS) and embedded devices.
• Use Tensorflow's Distribution Strategies to parallelize learning.
• Low-level Tensorflow, gradient tape, and how to build your custom models.
• Natural Language Processing (NLP) with Deep Learning.
• Demonstrate Moore's Law using Code.
• Transfer Learning to create state-of-the-art image classifiers.
• Deep Learning has been responsible for some amazing achievements recently, such as:
• Generating beautiful, photo-realistic images of people and things that never existed (GANs)
• Beating world champions in the strategy game Go, and complex video games like CS: GO and Dota 2 (Deep Reinforcement Learning)
• Self-driving cars (Computer Vision)
• Speech recognition (e.g. Siri) and machine translation (Natural Language Processing)
• Even creating videos of people doing and saying things they never did (DeepFakes - a potentially nefarious application of deep learning)

You can take Tensorflow 2.0: Deep Learning and Artificial Intelligence Certificate Course on Udemy.

4. Understanding the Foundations of TensorFlow

This course introduces TensorFlow, an open-source data flow library for numerical computations using data flow graphs.

Course rating: 4.5 out of 5.0 ( 138 Ratings total)

In this course, you will :

• Learn the TensorFlow library from very first principles.
• First, you'll start with the basics of machine learning using linear regression as an example and focuses on understanding fundamental concepts in TensorFlow.
• Next, you'll discover how to apply them to machine learning, the concept of a Tensor, the anatomy of a simple program, basic constructs such as constants, variables, placeholders, sessions, and the computation graph.
• Then, you'll be introduced to TensorBoard, the visualization tool used to view and debug the data flow graphs.
• You'll work with basic math operations and image transformations to see how common computations are performed.
• Finally, you'll solve a real-world machine learning problem using the MNIST handwritten dataset and the k-nearest-neighbors algorithm.
• By the end of this course, you'll have a better understanding of the foundations of TensorFlow.

You can take Understanding the Foundations of TensorFlow Certificate Course on Pluralsight.

5. Complete Tensorflow 2 and Keras Deep Learning Bootcamp

Learn to use Python for Deep Learning with Google's latest Tensorflow 2 library and Keras!

Course rating: 4.6 out of 5.0 ( 2,403 Ratings total)

In this course, you will :

• Learn to use TensorFlow 2.0 for Deep Learning.
• Leverage the Keras API to quickly build models that run on Tensorflow 2.
• Perform Image Classification with Convolutional Neural Networks.
• Use Deep Learning for medical imaging.
• Forecast Time Series Data with Recurrent Neural Networks.
• Use Generative Adversarial Networks (GANs) to generate images.
• Use deep learning for style transfer.
• Generate text with RNNs and Natural Language Processing.
• Serve Tensorflow Models through an API.
• Use GPUs for accelerated deep learning.

You can take Complete Tensorflow 2 and Keras Deep Learning Bootcamp Certificate Course on Udemy.

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In case you liked this article, you can also visit the following posts of mine;

• Best AngularJS Courses
• Best Apache Kafka Courses

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