Getting Started with Decision Trees
BeginnerLevel
1 hrs 0 minsDuration
About this Course
- Learn the basics of Decision Trees and why they are popular among data scientists.
- Understand the terminologies of decision trees like Leaf Node, Parent Node, and Pruning.
- Explore splitting criteria like Gini, Information Gain, and Chi-Square and more with our course.
Learning Outcomes
Decision Trees
Understand the philosophy and algorithm behind decision trees.
Classification Problems
Use decision trees for solving classification and regression problems.
Python Implementation
Implement Decision Trees in Python with best practices.
Who Should Enroll
- Both beginners and experienced professionals who want to build and optimize machine learning models.
- Foundational understanding of machine learning concepts who want to deepen their knowledge of decision trees.
- With Python programming looking to apply their skills in building decision tree models for data analysis.
Course Curriculum
Learn Decision Tree algorithm with their techniques and its in-depth implementation in Python with real-world analysis. Master classification problems using decision trees through hands-on practice.
1. Introduction to Decision Tree
2. Purity in Decision Trees
3. Terminologies Related to Decision Trees
4. How to Select the Best Split Point
5. Chi-Square
6. Information Gain
7. Reduction in Variance
8. Optimizing Performance of Decision Trees
9. Decision Tree Implementation
10. Where to go from here?
Get this Course Now
With this course you’ll get
- 30 hour
Duration
- Kunal Jain
Instructor
- Beginner
Level
Certificate of completion
Earn a professional certificate upon course completion
- Globally recognized certificate
- Verifiable online credential
- Enhances professional credibility
Frequently Asked Questions
Looking for answers to other questions?
This course is for people who wants to learn the most commonly used tree based algorithm: Decision Tree algorithm along with its implementation in Python.
The course assumes prior background in Machine Learning. So we would recommend you to be aware of basics of Machine Learning before going through this course.
This is a free course in Data Science. You only need to enrol in this free data science course and will be able to access the Decision Tree resources.
Once you register, you will have 6 month access to complete the course. If you visit the course 6 month after your initial registration - you will need to enroll in the course again. Your past progress will be lost.
You can complete 'Getting Started with Decision Trees' course in a few hours. You are also expected to apply Decision Trees and learning of this course to solve machine learning problems. The time taken in projects varies from person to person.
You can start by doing the tests at the end of various chapters. In addition, you can apply Decision Trees to solve various Practice problems on Analytics Vidhya DataHack Platform.
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