Home Big-data-and-business-intelligence Applied Deep Learning with TensorFlow and Google Cloud AI [Video]

Applied Deep Learning with TensorFlow and Google Cloud AI [Video]

By Christian Fanli Ramsey , Haohan Wang
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Mobile App with offline access
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60+ curated reading lists for various learning paths
50+ new titles added every month on new and emerging tech
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50+ new titles added every month on new and emerging tech
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Mobile App with offline access
What do you get with a Packt Subscription?
This book & 6500+ ebooks & video courses on 1000+ technologies
60+ curated reading lists for various learning paths
50+ new titles added every month on new and emerging tech
Early Access to eBooks as they are being written
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Customised display settings for better reading experience
50+ new titles added every month on new and emerging tech
Playlists, Notes and Bookmarks to easily manage your learning
Mobile App with offline access
What do you get with eBook?
Download this book in EPUB and PDF formats
Access this title in our online reader
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Online reader with customised display settings for better reading experience
What do you get with video?
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What do you get with video?
Stream this video
Access this title in our online reader
DRM FREE - Watch whenever, wherever and however you want
Online reader with customised display settings for better learning experience
What do you get with Audiobook?
Download a zip folder consisting of audio files (in MP3 Format) along with supplementary PDF
What do you get with Exam Trainer?
Flashcards, Mock exams, Exam Tips, Practice Questions
Access these resources with our interactive certification platform
Mobile compatible-Practice whenever, wherever, however you want
About this video

Deep Learning uses a cascade of multiple layers of nonlinear processing units for feature extraction and transformation on large volumes of data in order to make decisions about high dimensional data.

If you're looking to scale out your Deep Learning models and deploy your model into production then look no further because this video course will help you get the most out of TensorFlow and Keras to accelerate the training of your Deep Learning models and deploy your model at scale on the Cloud. Tools and frameworks such as TensorFlow, Keras, and Google Cloud MLE are used to showcase the strengths of various approaches, trade-offs, and building blocks for creating, training and evaluating your distributed deep learning models with GPU(s) and deploying your model to the Cloud. You will learn how to design and train your deep learning models and scale them out for larger datasets and complex neural network architectures on multiple GPUs using Google Cloud ML Engine. You’ll learn distributed techniques such as how parallelism and distribution work using low-level TensorFlow and high-level TensorFlow APIs and Keras.

Towards the end of the course, you will develop, train, and deploy your models using TensorFlow and Google Cloud Machine Learning Engine.

The code bundle for this video course is available at - https://github.com/PacktPublishing/Applied-Deep-Learning-with-TensorFlow-and-Google-Cloud-AI

Style and Approach

This video course adopts a tutorial-like approach to provide the right blend of theory,practical, and best practices in this rapidly developing area while providing a grounding in essential concepts that remain timeless and practical.

Publication date:
July 2018
Publisher
Packt
Duration
5 hours 57 minutes
ISBN
9781788621601

About the Authors
  • Christian Fanli Ramsey

    Christian Fanli Ramsey is an applied data scientist at IDEO. He is currently working at Greenfield Labs a research center between IDEO and Ford that focuses on the future of mobility. His primary focus on understanding complex emotions, stress levels and responses by using deep learning and machine learning to measure and classify psychophysiological signals.

    Christian and Haohan together they make dyadxmachina and their focus area is at the interaction of deep learning and psychophysiology, which means they mainly focus on 2 areas:

    • They want to help further intelligent systems to understand emotions and mood states of their users so they can react accordingly
    • They also want to help people understand their emotions, stress responses, mood states and how they vary over time in order to help people become more emotionally aware and resilient

    Browse publications by this author
  • Haohan Wang

    Haohan Wang is a deep learning researcher. Her focus is using machine learning to process psychophysiological data to understand people’s emotions and mood states to provide support for people’s well-being. She has a background in statistics and finance and has continued her studies in deep learning and neurobiology.

    Christian and Haohan together they make dyadxmachina and their focus area is at the interaction of deep learning and psychophysiology, which means they mainly focus on 2 areas:

    • They want to help further intelligent systems to understand emotions and mood states of their users so they can react accordingly
    • They also want to help people understand their emotions, stress responses, mood states and how they vary over time in order to help people become more emotionally aware and resilient

    Browse publications by this author
Latest Reviews (2 reviews total)
While I'm attending to lectures online and when I pause the video, network connections are broken so easily. Refreshing the page is my current workaround. But it's annoying.
cannot use packt mobile app to see this. mobile app displays only subscriptions, this is a one time purchase. There is no menu to navigate to one time purchases. mobile app keep displaying ads to subscribe. when you cllick link in email to see video/learn, it redirects to packt website and keeps asking if account info is correct, there is no way to fiind the courses you purched online too.
Applied Deep Learning with TensorFlow and Google Cloud AI [Video]
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