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TensorFlow 1.x Deep Learning Cookbook By Antonio Gulli, Amita Kapoor Take the next step in implementing various common and. Free eBook to Learning Python Learn to code like a professional with Python - an Request Your Free eBook Now: See All Resources from: Packt Publishing. Free eBook to Learning Python Learn to code like a professional with Python - an open source, versatile, and powerful Offered Free by: Packt Publishing See All Resources from: Packt Publishing · Request Download the TradePub App.

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Launching Visual Studio Latest commit d11f Mar 24, Free Learning Packt Publishing script packt-cli is a Python script that allows to automatically grab and download a daily Free Learning Packt ebook from https: Installation To install current version of script simply run pip install packt --upgrade You may want to install it inside new virtualenv.

Usage The packt-cli script might be executed with several optional arguments.

Download packt ebook free

To download all ebooks in all available formats from your Packt account, you have to prepare your config file as shown below: Click Continue , then Go to credentials. On the Add credentials to your project page , click the Cancel button.

Free ebooks: Machine Learning with Python and Practical Data Analysis

At the top of the page, select the OAuth consent screen tab. Select an email address, enter a product name if not already set, and click the Save button.

Free packt download ebook

Click OK to dismiss the resulting dialog. Create credentials folder: Simply, just fire up the script with -sgd argument; During first launch you will see a prompt in your browser asking for permissions, click then allow packt-cli -sgd Or if you're unable to launch browser locally e. Already done!

Download free packt ebook

Very true; I was trying to avoid Packt for the same reason. Recently, friend of mine shown two books that changed my perception.

They're really good IMHO: Can anybody recommend some books put out by Packt?

I've looked at quite a few of their books over the years, and they have been, without exception, dreadful not quite a tutorial, but also not a reference, lacking in detail, and usually behind the curve technology-wise. They appear to have several hundred books so there must be some hidden gems.

Good call, thanks. Really any JS book by Stoyan is pretty high quality. I have got the "NHibernate 3.

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Well it has many solutions and best practices. The print is not top notch - but the content is great. WebGL Beginner's Guide seems good, although the subject is fairly niche.

Free download ebook packt

I would strongly recommend against giving these guys your email address. I once bought a book from them and have had to ask them to take me off their mailing list 8 times now over a 3-year period. Got all the way through finding a book I was interested in whoever said check the reviews, thank you, a couple I was interested in were slated , then clicking for the download link and then Possibly demand has exceeded expectation.

If their website is down you can browse their books on amazon So it seems that in 2 days time their's entire catalog will be downloadable for free on the torrent sites: What makes you think it's not there already?

With a problem-solution approach, you will understand how to implement different deep neural architectures to carry out complex tasks at work.

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You will not only learn about the different mobile and embedded platforms supported by TensorFlow but also how to set up cloud platforms for deep learning applications. By using crisp, no-nonsense recipes, you will become an expert in implementing deep learning techniques in growing real-world applications and research areas such as reinforcement learning, GANs, autoencoders and more.

Click here to get the free eBook. This book will address the problems related to accurate and efficient data classification and prediction. Over the course of 7 days, you will be introduced to seven algorithms, along with exercises that will help you learn different aspects of machine learning. You will see how to pre-cluster your data to optimize and classify it for large datasets.

You will then find out how to predict data based on the existing trends in your datasets.

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This book covers algorithms such as: On completion of the book, you will understand which machine learning algorithm to pick for clustering, classification, or regression and which is best suited for your problem.

In this book, you will explore, in depth, topics such as data mining, classification, clustering, regression, predictive modeling, anomaly detection, boosted trees with XGBOOST, and more. With a slow learning curve on topics such as neural networks, you will explore deep learning, and more.

By the end of this book, you will be able to perform machine learning with R in the cloud using AWS in various scenarios with different datasets.