This course is designed for those interested to learn how to program an image recognition feature using Python. Read more.
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. Sev
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Get Started with All Access PassBuy Only This CourseAbout This Course
Who is the target audience?
- Beginners who want to learn to use Artificial Intelligence
- Prior coding experience is helpful
- Topics involve intermediate math, so familiarity with university-level math is very helpful
What will I 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
What are the requirements?
- PyCharm Community Edition 2017.2.3
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 a 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.Â
One farmer used the machine model to pick cucumbers!Â
Our Promise to You
By the end of this course, you will have learned how to program image-recognition feature using Python.
10 Day Money Back Guarantee. If you are unsatisfied for any reason, simply contact us and we’ll give you a full refund. No questions asked.
Get started today and learn more about programming image recognition feature using Python.
Course Curriculum
| Section 1 - Introduction | |||
| Course Trailer | 00:00:00 | ||
| What Is Python Artificial Intelligence? | 00:00:00 | ||
| Downloadable Source Files | 00:00:00 | ||
| Section 2 - Python Basics | |||
| Installing Python And Pycharm | 00:00:00 | ||
| How To Use Pycharm | 00:00:00 | ||
| Intro And Variables | 00:00:00 | ||
| Multi-Value Variables | 00:00:00 | ||
| Control Flow | 00:00:00 | ||
| Functions | 00:00:00 | ||
| Classes And Wrap Up | 00:00:00 | ||
| Source Files | 00:00:00 | ||
| Section 3 - TensorFlow Basics | |||
| Installing TensorFlow | 00:00:00 | ||
| Intro And Set Up | 00:00:00 | ||
| What Is TensorFlow | 00:00:00 | ||
| Constant And Operation Nodes | 00:00:00 | ||
| Placeholder Nodes | 00:00:00 | ||
| Variable Nodes | 00:00:00 | ||
| How To Create Linear Regression Model | 00:00:00 | ||
| Building Linear Regression Model | 00:00:00 | ||
| Source Files | 00:00:00 | ||
| Section 4 - Image Recognition (CIFAR-10 Project) | |||
| Introduction | 00:00:00 | ||
| Project Overview | 00:00:00 | ||
| Important CIFAR Packages | 00:00:00 | ||
| Displaying Images With PIL | 00:00:00 | ||
| Retrieving CIFAR 10 Data | 00:00:00 | ||
| Installing Matplotlib | 00:00:00 | ||
| Playing With CIFAR Images | 00:00:00 | ||
| Building The Model | 00:00:00 | ||
| Building Training Data And Training The Model | 00:00:00 | ||
| Testing The Model | 00:00:00 | ||
| Source Files | 00:00:00 | ||
About This Course
Who is the target audience?
- Beginners who want to learn to use Artificial Intelligence
- Prior coding experience is helpful
- Topics involve intermediate math, so familiarity with university-level math is very helpful
What will I 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
What are the requirements?
- PyCharm Community Edition 2017.2.3
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 a 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.Â
One farmer used the machine model to pick cucumbers!Â
Our Promise to You
By the end of this course, you will have learned how to program image-recognition feature using Python.
10 Day Money Back Guarantee. If you are unsatisfied for any reason, simply contact us and we’ll give you a full refund. No questions asked.
Get started today and learn more about programming image recognition feature using Python.
Course Curriculum
| Section 1 - Introduction | |||
| Course Trailer | 00:00:00 | ||
| What Is Python Artificial Intelligence? | 00:00:00 | ||
| Downloadable Source Files | 00:00:00 | ||
| Section 2 - Python Basics | |||
| Installing Python And Pycharm | 00:00:00 | ||
| How To Use Pycharm | 00:00:00 | ||
| Intro And Variables | 00:00:00 | ||
| Multi-Value Variables | 00:00:00 | ||
| Control Flow | 00:00:00 | ||
| Functions | 00:00:00 | ||
| Classes And Wrap Up | 00:00:00 | ||
| Source Files | 00:00:00 | ||
| Section 3 - TensorFlow Basics | |||
| Installing TensorFlow | 00:00:00 | ||
| Intro And Set Up | 00:00:00 | ||
| What Is TensorFlow | 00:00:00 | ||
| Constant And Operation Nodes | 00:00:00 | ||
| Placeholder Nodes | 00:00:00 | ||
| Variable Nodes | 00:00:00 | ||
| How To Create Linear Regression Model | 00:00:00 | ||
| Building Linear Regression Model | 00:00:00 | ||
| Source Files | 00:00:00 | ||
| Section 4 - Image Recognition (CIFAR-10 Project) | |||
| Introduction | 00:00:00 | ||
| Project Overview | 00:00:00 | ||
| Important CIFAR Packages | 00:00:00 | ||
| Displaying Images With PIL | 00:00:00 | ||
| Retrieving CIFAR 10 Data | 00:00:00 | ||
| Installing Matplotlib | 00:00:00 | ||
| Playing With CIFAR Images | 00:00:00 | ||
| Building The Model | 00:00:00 | ||
| Building Training Data And Training The Model | 00:00:00 | ||
| Testing The Model | 00:00:00 | ||
| Source Files | 00:00:00 | ||
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