This course is designed for those interested to learn how to program fraud detection using Python, TensorFlow and linear regression. 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 this course is for:
- 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 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 a Credit Card Fraud Detection Model in Python. Learn how to keep your data safe!
Requirements:
- PyCharm Community Edition 2017.2.3
Do you want to learn how to use Artificial Intelligence (AI) for automation? In this course, we cover coding in Python, working with TensorFlow, and analyzing credit card fraud. 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. 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 fraud detection using Python, TensorFlow, and linear regression.
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 with Python, TensorFlow and linear regression for fraud detection.
Course Curriculum
| Section 1 - Introduction | |||
| Course Trailer | 00:00:00 | ||
| What Is Python Artificial Intelligence? | 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 Regression Model | 00:00:00 | ||
| Building Linear Regression | 00:00:00 | ||
| Source Files | 00:00:00 | ||
| Section 4 - Fraud Detection (Credit Card) | |||
| Introduction | 00:00:00 | ||
| Project Overview | 00:00:00 | ||
| Introducing Dataset | 00:00:00 | ||
| Building Training – Testing Datasets | 00:00:00 | ||
| Eliminating Datasets Bias | 00:00:00 | ||
| Building The Computational Graph | 00:00:00 | ||
| Building Functions To Connect Graph | 00:00:00 | ||
| Training The Model | 00:00:00 | ||
| Testing Model | 00:00:00 | ||
| Source Files | 00:00:00 | ||
About This Course
Who this course is for:
- 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 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 a Credit Card Fraud Detection Model in Python. Learn how to keep your data safe!
Requirements:
- PyCharm Community Edition 2017.2.3
Do you want to learn how to use Artificial Intelligence (AI) for automation? In this course, we cover coding in Python, working with TensorFlow, and analyzing credit card fraud. 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. 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 fraud detection using Python, TensorFlow, and linear regression.
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 with Python, TensorFlow and linear regression for fraud detection.
Course Curriculum
| Section 1 - Introduction | |||
| Course Trailer | 00:00:00 | ||
| What Is Python Artificial Intelligence? | 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 Regression Model | 00:00:00 | ||
| Building Linear Regression | 00:00:00 | ||
| Source Files | 00:00:00 | ||
| Section 4 - Fraud Detection (Credit Card) | |||
| Introduction | 00:00:00 | ||
| Project Overview | 00:00:00 | ||
| Introducing Dataset | 00:00:00 | ||
| Building Training – Testing Datasets | 00:00:00 | ||
| Eliminating Datasets Bias | 00:00:00 | ||
| Building The Computational Graph | 00:00:00 | ||
| Building Functions To Connect Graph | 00:00:00 | ||
| Training The Model | 00:00:00 | ||
| Testing Model | 00:00:00 | ||
| Source Files | 00:00:00 | ||
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