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Tensorflow on Google's Cloud Platform for Data Engineers
Rating: 4.2 out of 5(47 ratings)
587 students

Tensorflow on Google's Cloud Platform for Data Engineers

The Fourth Course in a Series for Attaining the Google Certified Data Engineer
Created byMike West
Last updated 8/2017
English

What you'll learn

  • You'll understand the basics of TensorFlow.
  • You'll be able to build TensorFlow models on Google's Cloud.
  • You'll be prepared for TensorFlow questions on the Google Certified Data Engineering Exam.
  • Upon completion you'll know how to build machine learning models inside Google's Cloud.

Course content

4 sections44 lectures1h 16m total length
  • Introduction1:25

    This course is about TensorFlow. 

    This is Google's computational engine for machine learning. 

  • Exam Update0:56

    In this lecture I discuss created a machine learning course for data engineers. 

    This course will be very targeted and specific to questions on the exam. 

  • Is this Course for You?1:36

    Is this course right for you? 

    Let's find out in this lesson. 

  • Instructor Course Q&A0:50

    In this lesson I answer a few questions about the course and the exam. 

  • What's an Array?1:18

    Let's define what an array is. 

    The very basics. 


  • What is a Multi-Dimensional Array or Tensor?1:24

    Tensors are multi-dimensional arrays. 

    Let's find out what that is in this lesson. 

  • How Tensors Flow1:01

    Tensors and nodes together create a TensorFlow network. 

    These networks are represented as graphs in TensorFlow. 

  • Real Numbers Flowing through our Graph1:04

    In this lesson let's add some real numbers to our graph. 

    This will help show how tensor move through the graph with data in them. 

  • Hello World in TensorFlow1:35

    Every programming language has hello world and TensorFlow is no different. 

    Let's walk through the most basic TensorFlow example we can. 

  • Course Downloads0:21
  • Summary0:23
  • Quiz

Requirements

  • A solid understanding of Python and the core libraries for machine learning.
  • A solid understanding of the principles of machine learning.
  • Strong familiarity with SQL
  • I'd highly recommend taking my data engineering courses in order.

Description

Welcome to Tensorflow on the Google Cloud Platform for Data Engineers This is the fourth course in a series of courses designed to help you attain the coveted Google Certified Data Engineer. 

Additionally, the series of courses is going to show you the role of the data engineer on the Google Cloud Platform

NOTE: This is not a course on how to develop machine learning models with TensorFlow. This is a very targeted course on TensorFlow for data engineers.  My goal is to give data engineers what they need to know for the exam and provide learners with the foundations of TensorFlow on Google's Cloud Platform. 

At this juncture the Google Certified Data Engineer is the only real world certification for data and machine learning engineers.

TensorFlow is an open source software library created by Goggle for doing graph-based computations quickly. It does this by utilizing the GPU(Graphics Processing Unit)  and also making it easy to distribute the work across multiple GPUs and computers.

Tensors, in general, are simply arrays of numbers, or functions, that transform according to certain rules under a change of conditions. Nodes in the graphs represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. 

In the course you'll discover how to apply TensorFlow to machine learning, the concept of a Tensor, the anatomy of a simple program, basic constructs such as constants, variables, placeholders, sessions and the computation graph.

You'll work with basic math operations and image transformations to see how common computations are performed.

You'll learn TensorFlow within the context of the Google Cloud Platform

                                                             *Five Reasons to take this Course.*

1) You Want to be a Data Engineer 

It's the number one job in the world. (not just within the computer space) The growth potential career wise is second to none. You want the freedom to move anywhere you'd like. You want to be compensated for your efforts. You want to be able to work remotely. The list of benefits goes on. 

2) The Google Certified Data Engineer 

Google is always ahead of the game. If you were to look back at a timeline of their accomplishments in the data space you might believe they have a crystal ball. They've been a decade ahead of everyone.  Now, they are the first and the only cloud vendor to have a data engineering certification. With their track record I'll go with Google. 

3) The Growth of Data is Insane 

Ninety percent of all the world's data has been created in the last two years. Business around the world generate approximately 450 billions transactions a day. The amount of data collected by all organizations is approximately 2.5 Exabytes a day. That number doubles every month. 

4) TensorFlow in Plain English

TensorFlow is a low level language.  The basic concept of a tenor is hard to grasp if you aren't familiar with neural networks. In the course we will break down TensorFlow in to bite sized pieces ensuring you learn the fundamentals first. After we've built a base understanding of tensors and how they flow we will move on to more complicated examples. 

5) You want to be ahead of the Curve 

The data engineer role is fairly new.  While your learning, building your skills and becoming certified you are also the first to be part of this burgeoning field.  You know that the first to be certified means the first to be hired and first to receive the top compensation package. 

Thank you for your interest in Tensorflow on the Google Cloud Platform for Data Engineers and we will see you in the course!!




Who this course is for:

  • If you're preparing for the Google Certified Data Engineering exam then this course is for you.
  • Anyone wanting to learn how to build TensorFlow models in Google's Cloud.