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Development Data Science TensorFlow

Google Cloud Machine Learning with TensorFlow

Train and predict your models using the Google Cloud ML Engine
Rating: 4.2 out of 54.2 (46 ratings)
211 students
Created by Packt Publishing
Last updated 12/2019
English
English
30-Day Money-Back Guarantee

What you'll learn

  • Get access to powerful computers with GPUs organized in clusters to optimize your performance
  • Train bigger models faster using the Google Cloud infrastructure
  • Explore machine types and learn how to configure clusters to solve problems
  • Train deep learning models using the Google Cloud AI Platform
  • Run classical machine learning algorithms with TensorFlow
  • Run your trained models to get predictions using the AI Platform API

Course content

6 sections • 40 lectures • 4h 2m total length

  • Preview06:49
  • Introduction to the Google Cloud Platform
    07:07
  • Getting a GCP Account
    02:16
  • Walking Through the GCP Console and Google Cloud SDK
    07:43
  • Google Compute and Google Storage
    05:49
  • AI Platform Overview
    02:55
  • Example Workflow with AI Platform Notebooks
    11:54
  • Test your knowledge
    5 questions

  • Preview07:45
  • Lab: Programming in TensorFlow
    08:53
  • Using TensorBoard
    03:44
  • Overview of Machine Learning
    06:27
  • Lab: Linear Regression on TensorFlow
    10:39
  • Logistic Regression
    04:31
  • Lab: Logistic Regression on TensorFlow
    05:35
  • K-Nearest Neighbor (KNN)
    03:57
  • Lab: KNN on TensorFlow
    06:44
  • Test your knowledge
    6 questions

  • Lab: Project Setup
    02:00
  • Lab: Staging Data and Preprocessing
    05:14
  • Model Training Using Keras API
    02:02
  • Lab: Testing Model Predictions
    03:50
  • Lab: Exporting the Model for Production
    04:29
  • Test your knowledge
    4 questions

  • Project Setup
    03:56
  • Lab: Staging Data and Preprocessing
    10:29
  • Defining the Model
    03:14
  • Lab: Defining the Distribution Strategy
    04:02
  • Lab: Distributed Training
    03:29
  • Lab: Monitor Learning Process in TensorBoard
    06:31
  • Test your knowledge
    5 questions

  • Overview: Methods for Serving TensorFlow Models on GCP
    15:07
  • Lab: Setting Up TensorFlow Serving
    01:47
  • Inference Using TensorFlow Serving
    07:02
  • Lab: Deploying Models to AI Platform
    05:49
  • Lab: Inference Using AI Platform
    05:27
  • Lab: Setting Up Cloud Functions for TensorFlow
    07:34
  • Lab: Inference Using Cloud Functions
    03:57
  • Test your knowledge
    4 questions

  • Introduction to Neural Network
    06:25
  • Feedforward and Activation Function
    03:37
  • Gradient Descent
    06:43
  • Backpropagation
    05:19
  • One Hot Encoding, Softmax, and Cross-Entropy
    07:30
  • Lab: Building a Simple Neural Network on TensorFlow
    14:21
  • Test your knowledge
    5 questions

Requirements

  • Familiarity with ML concepts will be advantageous.

Description

TensorFlow has become the first choice for deep learning tasks because of the way it facilitates building powerful and sophisticated neural networks. The Google Cloud Platform is a great place to run TF models at scale, and perform distributed training and prediction.

This course shows you how to use Google Cloud to train TensorFlow models and use them to predict results for multiple users. You will learn to efficiently train neural networks using large datasets and to serve your training models.

With this video course, you will use the power of Google's Cloud Platform to train deep neural networks faster. This course supplies various examples of training in Google Cloud AI Platform. You will also learn to run predictions for your model using the cloud. You will explore topics such as cloud infrastructures, distributed training, serverless technologies, model serving, and more.

By the end of the course, you will be expert at training and serving neural models, and beyond.

About the Author

Tobias Zwingmann is Senior Data Scientist at Deutsche Messe AG and possesses a high entrepreneurial bias. In his work, he utilizes small and big data to create value—for example, by turning analytical insights into better customer experience and higher customer engagement. He also supports the development of new data-driven businesses and prototypes new data products for his organization. He likes to learn from and meet open-minded people.

Who this course is for:

  • This course targets data scientists, people starting their journey in the ML/DL domain, and anyone keen to start training deep neural networks using cloud infrastructures.

Instructor

Packt Publishing
Tech Knowledge in Motion
Packt Publishing
  • 3.9 Instructor Rating
  • 58,076 Reviews
  • 350,252 Students
  • 1,418 Courses

Packt has been committed to developer learning since 2004. A lot has changed in software since then - but Packt has remained responsive to these changes, continuing to look forward at the trends and tools defining the way we work and live. And how to put them to work.

With an extensive library of content - more than 4000 books and video courses -Packt's mission is to help developers stay relevant in a rapidly changing world. From new web frameworks and programming languages, to cutting edge data analytics, and DevOps, Packt takes software professionals in every field to what's important to them now.

From skills that will help you to develop and future proof your career to immediate solutions to every day tech challenges, Packt is a go-to resource to make you a better, smarter developer.

Packt Udemy courses continue this tradition, bringing you comprehensive yet concise video courses straight from the experts.



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