Machine Learning with TensorFlow
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VIDEO TUTORIAL Machine Learning with TensorFlow

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Tackle common machine learning problems with Google’s TensorFlow library and build deployable solutions

About This Machine Learning with TensorFlow Video course

  • Use raw real-world data to create pipelines to train and apply classifiers using TenserFlow
  • Productionize challenges and solutions
  • Go through a full lifecycle of a TensorFlow solution with a practical demonstration ofsystem setup, training, validation, and creating pipelines for the real world

Machine Learning with TensorFlow In Detail

TensorFlow is an open source software library for numerical computation using data flow graphs. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.

This video tutorial addresses common commercial machine learning problems using Google’s TensorFlow library. It will not only help you discover what TensorFlow is and how to use it, but will also show you the unbelievable things that can be done in machine learning with the help of examples/real-world use cases.

We start off with the basic installation of Tensorflow, moving on to covering the unique features of the library such as Data Flow Graphs, training, and visualization of performance with TensorBoard—all within an example-rich context using problems from multiple sources.. The focus is on introducing new concepts through problems that are coded and solved over the course of each section.

What will you learn in this course?

Course plan
Chapter 1
Getting Started with Deep Learning
Chapter 2
Your First Classifier
Chapter 3
The TensorFlow Toolbox
Chapter 4
Cats and Dogs – Convolutional Neural Networks

Detailed course plan

Chapter 1 : Getting Started with Deep Learning
18m28
 
Lesson 1The Course Overview
Lesson 2Introducing Deep Learning
Lesson 3Installing TensorFlow on Mac OSX
Lesson 4Installation on Windows – Pre-Reqeusite Virtual Machine Setup
Lesson 5Installation on Windows/Linux
Chapter 2 : Your First Classifier
16m39
 
Lesson 1The Hand-Written Letters Dataset
Lesson 2Automating Data Preparation
Lesson 3Understanding Matrix Conversions
Lesson 4The Machine Learning Life Cycle
Lesson 5Reviewing Outputs and Results
Chapter 3 : The TensorFlow Toolbox
20m42
 
Lesson 1Getting Started with TensorBoard
Lesson 2TensorBoard Events and Histograms
Lesson 3The Graph Explorer
Lesson 4Our Previous Project on TensorBoard
Chapter 4 : Cats and Dogs – Convolutional Neural Networks
18m52
 
Lesson 1Fully Connected Neural Networks
Lesson 2Convolutional Neural Networks
Lesson 3Programming a CNN
Lesson 4Using TensorBoard on Our CNN
Lesson 5CNN Versus Fully Connected Network Performance

Your questions about the course

With which software version is this tutorial compatible with?

Tensorflow

What is the required level to follow this tutorial ?

intermediate

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