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Hands-On Image Recognition: Python Data Science Bootcamp

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...

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Course Description

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...

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!

What you’ll learn
  • learn how to perform automated image recognition
  • you learn how to code in Python
  • calculate linear regression with TensorFlow
  • AI is code that mimics certain tasks

Covering Topics

1
Section 1 : Introduction
2
Section 2 : Python Basics
3
Section 3 : TensorFlow Basics
4
Section 4 : Image Recognition (CIFAR-10 Project)

Curriculum

      Section 1 : Introduction
1
What is Python Artificial Intelligence?
      Section 2 : Python Basics
2
Installing Python and Pycharm
3
How to use Pycharm
4
Intro and Variables Preview
5
Multi-value Variables
6
Control Flow
7
Functions
8
Classes and Wrap Up
      Section 3 : TensorFlow Basics
9
Intro and Set up Preview
10
What is TensorFlow
11
Constant and Operation Nodes
12
Placeholder Nodes
13
Variable Nodes
14
How to Create Linear Regression Model
15
Building Linear Regression Model
      Section 4 : Image Recognition (CIFAR-10 Project)
16
Introduction Preview
17
Project Overview
18
Important CIFAR Packages
19
Displaying Images with PIL
20
Retrieving CIFAR 10 Data
21
Playing with CIFAR Images
22
Building the Model
23
Building Training Data and Training the Model
24
Testing the Model

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