How to Build Decision Tree from Scratch with Python | Decision Tree in Machine Learning | Codegnan
Learn about Building a Decision Tree on Machine Learning from scratch using Python. Decision tree learning uses a decision tree (as a predictive model) to go from observations about an item (represented in the branches) to conclusions about the item's target value (represented in the leaves).
Source code link : https://drive.google.com/drive/folder...
Agenda:
1. What is Decision Tree?
2. Why Machine Learning is used in building a Decision Tree?
3. Importance of Machine Learning in making a Decision Tree?
4. Using Decision Tree Algorithm in Machine Learning
4. How to relate Classification to real world problems?
5. How can we relate Decision Trees to our general activities?
6. Different Algorithms to build a Simple Decision Tree from Scratch
7. Building a Simple Decision Tree Model from scratch using Python.
8. Understanding the real life applications of Classification.
Machine Learning the buzz word of 21st century,which people often think that it is not related to their field,as they only picture a robot:a dependable butler or a deadly Terminator depending on who you ask.But the unknown fact it is already into our daily life applications like Email Spam Filters, Fraud Detection, Recommendation Engine, Intelligent Assistants like Siri, Alexa, Ok Google.
Whenever you perform classification, the first step is to understand the problem and identify potential features and labels. Features are those characteristics or attributes which affect the results of the label
In this webinar you will understand the importance of Classification and how classification can be related to real world problems.You are going to understand how simple Decision Trees are as they can be related to if..else conditional statements in Python.As it is all about how to align or place such if..else conditions.
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