About This Course
Do you want to predict the stock market using artificial intelligence? Join us in this course for beginners in automating tasks.
In this course, you learn how to code in Python, calculate linear regression with TensorFlow, and make a stock market prediction app. 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.
What are the requirements?
- PyCharm Community Edition 2017.2.3.
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 app with Python that uses data to predict the stock market.
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.
Our Promise to You
By the end of this course, you will have learned how to build a stock market prediction app with artificial intelligence.
30 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 building a stock market prediction app.
|Section 1 - Introduction|
|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|
|Classes And Wrap-up||00:00:00|
|Section 3 - TensorFlow Basics|
|Intro And Setup||00:00:00|
|What Is TensorFlow?||00:00:00|
|Constant And Operation Nodes||00:00:00|
|How To Create A Linear Regression Model||00:00:00|
|Building A Linear Regression Model||00:00:00|
|Section 4 - Stock Market Prediction: Project|
|Importing And Formatting Data We Want||00:00:00|
|Calculating Price Differences||00:00:00|
|Building A Computational Graph||00:00:00|
|Training A Model||00:00:00|
|Testing Model Accuracy||00:00:00|
|Summary And Outro||00:00:00|