Coursera – TensorFlow: Advanced Techniques Specialization 2021-2

Description

TensorFlow: Advanced Techniques Specialization is a TensorFlow library training course. TensorFlow is an open source machine learning platform with a complete and flexible ecosystem of tools and libraries. Using TensorFlow, researchers are able to take advantage of the latest machine learning achievements, and developers can equip their applications with machine learning power. The main applications of TensorFlow are in applications such as voice recognition, Google Translate, image recognition and natural language processing. This course is recommended for all software and machine learning engineers who have a basic understanding of TensorFlow and seek to expand their knowledge and skills by learning the advanced features of TensorFlow.

This course is divided into 4 sub-courses, during which you will gain practical and applied knowledge of TensorFlow. In the first part, you will understand the basics of the Functional API and build non-sequential models, personalized loss functions, and different layers. In the second part, you will learn how optimization works, as well as how to use GradientTape and Autograph, and improve the training process in different environments with multiple chips and processors. The third part is to recognize and practice advanced computer vision scenarios such as object recognition, image fragmentation and image interpretation of twists, and the fourth part is to explore productive in-depth learning and how to use artificial hashes to generate new content, automatic encryption, VAEs And dedicated GANs.

What are you learning?

Understand the basics of the Functional API and build odd non-sequential models, loss functions and layers

Learn to optimize in different situations and use GradientTape and Autograph

Practice object recognition, image segmentation, and visual interpretation of twists

Explore in-depth manufacturer learning to create new content, from style transitions to Ventilator-Associated Events algorithms or VAEs and Generative adversarial networks or GANs

What skills do you acquire?

Model interpretation

Training loops, loss function and personalized layers

Distribution strategies

Functional API and build personal and weird models with it

Use GradientTape for optimization

And …

Specifications of TensorFlow: Advanced Techniques Specialization

Publisher: Coursera

Instructor: Laurence Moroney, Eddy Shyu

English language

Level of education: Intermediate

Number: 4 courses

Course duration: with a suggested time of 6 hours per week, approximately 5 months

Prerequisites

Learners should have a working knowledge of AI and deep learning. They should have intermediate Python skills (understanding of decorators and context managers is preferred) as well as some experience with any deep learning framework (TensorFlow, Keras, or PyTorch). Learners should be proficient in basic calculus, linear algebra, and statistics.

We highly recommend that you complete theDeep Learning Specialization prior to starting this Specialization.

Installation

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English subtitle

Quality: 720p