Introduction to AI with Python
Decision trees exercise
A course by Rodrigo Montemayor , Programmer
About the video: Decision trees exercise
Overview
“Finally, we will create a mini project using the decision tree algorithm, applying all the actual machine learning process.”
In this video lesson Rodrigo Montemayor addresses the topic: Decision trees exercise, which is part of the Domestika online course: Introduction to AI with Python. Learn the basics of artificial intelligence and how to apply it in problem-solving.
Partial transcription of the video
“In this lesson. we will create a project using the decision tree algorithm. ensuring we apply the entire Machine Learning process. Let's begin. In our exercise. we'll base it on the logistic regression task. You can either duplicate the sheet in or replicate the file if you're working with Visual Studio Code. This will serve as our foundation for We will click on create a copy. And I will call this method decision trees. definitively. First. we will thoroughly review all our materials. aiming to eliminate the training and prediction This step is crucial for refining our approach moving forw...”
This transcript is automatically generated, so it may contain mistakes.
Course summary for: Introduction to AI with Python
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Category
Artificial Intelligence, Web & App Design -
Areas
AI programming, Artificial Intelligence, Programming, Web Development
Rodrigo Montemayor
A course by Rodrigo Montemayor
Rodrigo Montemayor has been a programmer for more than 20 years. He has worked with many of the largest companies in Mexico and also some international ones in web, mobile, and desktop development. In addition, through his own company, he has created software for all types of clients, such as various technology brands, cybersecurity, automation, and artificial intelligence.
On the other hand, he shares content on the RingaTech Youtube channel with the aim of teaching and informing about technology, cybersecurity, and artificial intelligence. As part of the channel, he has developed some projects and games whose code is available to the public.
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