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30-Day Money-Back Guarantee

This course includes:

  • 8.5 hours on-demand video
  • 12 articles
  • 8 downloadable resources
  • Full lifetime access
  • Access on mobile and TV
Development Data Science Python

Build and train a data model to recognize objects in images!

Make an image recognition model with TensorFlow & Python predictive modeling, regression analysis & machine learning!
Rating: 4.3 out of 54.3 (184 ratings)
1,361 students
Created by Mammoth Interactive, John Bura
Last updated 1/2019
English
30-Day Money-Back Guarantee

What you'll learn

  • Learn how to code in Python, a popular coding language used for websites like YouTube and Instagram.
  • Learn TensorFlow and how to build models of linear regression.
  • Make an image recognition model with CIFAR.

Course content

11 sections • 57 lectures • 8h 25m total length

  • Preview05:00

  • Preview05:18
  • How to Use PyCharm
    05:16
  • Intro and Variables
    11:49
  • Multi-value Variables
    23:15
  • Control Flow
    29:08
  • Functions
    14:19
  • Classes and Wrap Up
    40:52
  • ($300 value!) Source Files
    00:01

  • Intro and Set up
    04:11
  • What is TensorFlow?
    13:28
  • Update! Importing TensorFlow to PyCharm
    04:25
  • FAQ: Help with TensorFlow Installation
    00:10
  • Constant and Operation Nodes
    14:26
  • Placeholder Nodes
    11:06
  • Variable Nodes
    08:22
  • How to Create Linear Regression Model
    05:48
  • Building Linear Regression Model
    24:18
  • ($300 value!) Source Files
    00:01

  • Introduction
    03:09
  • Project Overview
    03:00
  • Important CIFAR Packages
    08:35
  • Displaying Images with PIL
    07:30
  • Retrieving CIFAR 10 Data
    09:32
  • Installing Matplotlib
    00:06
  • Playing with CIFAR Images
    08:56
  • Building the Model
    14:13
  • Building Training Data and Training the Model
    08:24
  • Testing the Model
    13:38
  • ($300 value!) Source Files
    00:01

  • Introduction to Machine Learning Neural Networks
    02:01
  • Introduction to Machine Learning
    10:56
  • Introduction to Neutral Networks
    10:23
  • Introduction to Convolutions
    13:43

  • Introduction to the Keras API
    01:49
  • Introduction to TensorFlow and Keras
    09:06
  • Understanding Keras Syntax
    18:46
  • Introduction to Activation Functions
    12:59

  • Introduction to Datasets and CIFAR-10
    01:53
  • Exploring CIFAR-10 Dataset
    08:36
  • Understanding Specific Data Points
    17:17
  • Formatting Input Images
    12:04

  • Introduction to the Image Classifier Model
    02:23
  • Building the Model
    17:52
  • Compiling and Training the Model
    12:38
  • Gradient Descent and Optimizer
    14:24

  • Introduction to Saving and Loading
    02:08
  • Saving and Loading Model to H5
    14:53
  • Saving Model to Protobuf File
    17:24
  • Bootcamp Summary
    05:40

  • Texts Assets: Understand Machine Learning Neural Networks
    00:01
  • Texts Assets: Explore the Keras API
    00:01
  • Asset Files: Format Datasets and Examine CIFAR-10
    00:01
  • Asset Files: Build the Image Classifier Model
    00:01
  • Asset Files: Save and Load Trained Models
    00:01

Requirements

  • Please download PyCharm Community Edition 2017.2.3.

Description

"Well done!!!!!! I found it the BEST source for me out of many to learn how to implement AI project due the facts it starts from the very basics of Python and TensorFlow and assumes no prior knowledge (or almost no prior knowledge) which should not be taken for granted since other courses do so. The instructor is wonderful and explains all the concepts wonderfully! Thank you so much! helped me a lot!"

"Very easy to understand. Loving it so far!" - Arthur G.

This course was funded by a wildly successful Kickstarter.

Let's learn how to perform automated image recognition! In this course, you learn how to code in Python, calculate linear regression with TensorFlow, and perform CIFAR 10 image data and recognition. We interweave theory with practical examples so that you learn by doing.

AI is code that mimics certain tasks. You can use AI to predict trends like the stock market. Automating tasks has exploded in popularity since TensorFlow became available to the public (like you and me!) AI like TensorFlow is great for automated tasks including facial recognition. One farmer used the machine model to pick cucumbers! 

Join Mammoth Interactive in this course, where we blend theoretical knowledge with hands-on coding projects to teach you everything you need to know as a beginner to image recognition.

Enroll today to join the Mammoth community!

Who this course is for:

  • Beginners who want to learn to use Artificial Intelligence.
  • Prior coding experience is helpful. For an in-depth intro to Python, search for our Ultimate Python Beginner Course.
  • Topics involve intermediate math, so familiarity with university-level math is very helpful.

Instructors

Mammoth Interactive
Top-Rated Instructor, 700,000+ Students
Mammoth Interactive
  • 4.2 Instructor Rating
  • 10,499 Reviews
  • 200,498 Students
  • 255 Courses

"I absolutely love this course. This is such a comprehensive course that was well worth the money I spent and a lot more. Will definitely be looking at more Mammoth Interactive courses when I finish this." – Student Matt W.

"Very good at explaining the basics then building to more complex features." – Student Kevin L.

Mammoth Interactive has been contracted to produce epic soundtracks, addicting levels, rock solid programming and business development.

John Bura
Best Selling Instructor Web/App/Game Developer 700k Students
John Bura
  • 4.2 Instructor Rating
  • 17,147 Reviews
  • 317,307 Students
  • 284 Courses

John Bura is has been a successful Udemy instructor since 2011. John Bura has been programming games since 1997 and teaching since 2002. John is the owner of the game development studio Mammoth Interactive. This company produces XBOX 360, iPhone, iPad, android, HTML 5, ad-games and more. Mammoth Interactive recently sold a game to Nickelodeon! John has been contracted by many different companies to provide game design, audio, programming, level design and project management. To this day John has 40 commercial games that he has contributed to. Several of the games he has produced have risen to the top 10 in the Apple's app store. In his spare time John likes to play ultimate Frisbee, cycle and work out.

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