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Machine Learning Projects with TensorFlow 2.0
Machine Learning Projects with TensorFlow 2.0

Machine Learning Projects with TensorFlow 2.0: Supercharge your Machine Learning skills with Tensorflow 2

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Profile Icon Dr. Vlad Sebastian Ionescu
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Full star icon Full star icon Full star icon Full star icon Full star icon 5 (1 Ratings)
Video Apr 2020 4hrs 20mins 1st Edition
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NZ$14.99 NZ$201.99
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Free Trial
Arrow left icon
Profile Icon Dr. Vlad Sebastian Ionescu
Arrow right icon
Free Trial
Full star icon Full star icon Full star icon Full star icon Full star icon 5 (1 Ratings)
Video Apr 2020 4hrs 20mins 1st Edition
Video
NZ$14.99 NZ$201.99
Subscription
Free Trial
Video
NZ$14.99 NZ$201.99
Subscription
Free Trial

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Key benefits

  • Make use of the amazing new feature of TensorFlow 2 called 'Eager Execution' which makes it easier to learn and use
  • Upgrade your skills by building real-world Machine Learning projects
  • Build, test and deploy different ML models and learn more modern techniques such as Reinforcement Learning and Transfer Learning

Description

TensorFlow is the world’s most widely adopted framework for Machine Learning and Deep Learning. TensorFlow 2.0 is a major milestone due to its inclusion of some major changes making TensorFlow easier to learn and use such as “Eager Execution”. It will support more platforms and languages, improved compatibility and remove deprecated APIs. This course will guide you to upgrade your skills in Machine Learning by practically applying them by building real-world Machine Learning projects. Each section should cover a specific project on a Machine Learning task and you will learn how to implement it into your system using TensorFlow 2. You will implement various Machine Learning techniques and algorithms using the TensorFlow 2 library. Each project will put your skills to test, help you understand and overcome the challenges you can face in a real-world scenario and provide some tips and tricks to help you become more efficient. Throughout the course, you will cover the new features of TensorFlow 2 such as Eager Execution. You will cover at least 3-4 projects. You will also cover some tasks such as Reinforcement Learning and Transfer Learning. By the end of the course, you will be confident to build your own Machine Learning Systems with TensorFlow 2 and will be able to add this valuable skill to your CV. Codefiles are uploaded here: https://github.com/PacktPublishing/Machine-Learning-Projects-with-TensorFlow-2.0

Who is this book for?

This course is for developers, data scientists and ML engineers who now want to enhance their skill set in Machine Learning using TensorFlow by building real-world projects. This course will appeal to someone who has a basic understanding of ML concepts, Python and TensorFlow.

What you will learn

  • Strengthen your foundations to build TensorFlow 2.0 projects by exploring its new features
  • Analyze the Titanic data set to obtain desired results with ease
  • Implement and organize your Tensorflow projects in a professional manner
  • Use Tensorboard to inspect various metrics and monitor your project's performance
  • Research and make the most of other people s Kaggle solutions
  • Use OpenAI Gym Environments for implementing state of the art reinforcement learning techniques using TF-Agents
  • Apply the latest Transfer Learning techniques from Tensorflow

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Apr 29, 2020
Length: 4hrs 20mins
Edition : 1st
Language : English
ISBN-13 : 9781838980252
Vendor :
Google
Category :
Languages :
Tools :

What do you get with a Packt Subscription?

Free for first 7 days. $19.99 p/m after that. Cancel any time!
Product feature icon Unlimited ad-free access to the largest independent learning library in tech. Access this title and thousands more!
Product feature icon 50+ new titles added per month, including many first-to-market concepts and exclusive early access to books as they are being written.
Product feature icon Innovative learning tools, including AI book assistants, code context explainers, and text-to-speech.
Product feature icon Thousands of reference materials covering every tech concept you need to stay up to date.
Subscribe now
View plans & pricing

Product Details

Publication date : Apr 29, 2020
Length: 4hrs 20mins
Edition : 1st
Language : English
ISBN-13 : 9781838980252
Vendor :
Google
Category :
Languages :
Tools :

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Table of Contents

5 Chapters
Regression Task Airbnb Prices in New York Chevron down icon Chevron up icon
Classification Task Build Real World Apps: Who Will Win the Next UFC? Chevron down icon Chevron up icon
Natural Language Processing Task: How to Generate Our Own Text Chevron down icon Chevron up icon
Reinforcement Learning Task: How to Become Best at Pacman Chevron down icon Chevron up icon
Transfer Learning Task: How to Build a Powerful Image Classifier Chevron down icon Chevron up icon

Customer reviews

Rating distribution
Full star icon Full star icon Full star icon Full star icon Full star icon 5
(1 Ratings)
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1 star 0%
ben Sep 23, 2023
Full star icon Full star icon Full star icon Full star icon Full star icon 5
this is the best video quickly to learn AI, with the Tensorflow library open-source will be widely supported. The author's instructions explain line by line, very easy to follow the programming logic.
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