AI/ML: Naive Bayes and Decision Tree -Module 3 Training

Live Online & Classroom Enterprise Certification Training

Delve into Naïve Bayes and Decision Tree algorithms essential for AI and machine learning. Learn their principles, applications in classification, algorithm construction, and practical implementation. Gain hands-on experience to effectively apply these techniques in real-world data analysis and model building.

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What is AI/ML: Naive Bayes and Decision Tree -Module 3 Course about?

This course focuses on Naïve Bayes and Decision Tree algorithms in AI and machine learning. Topics include the principles of classification, algorithm construction, pruning techniques, and practical implementation. Participants will gain hands-on experience to apply these techniques effectively for building predictive models.

What are the objectives of AI/ML: Naive Bayes and Decision Tree -Module 3 Course ?

The objective of this course is to equip participants with a deep understanding of Naïve Bayes and Decision Tree algorithms in AI and machine learning. By the end of the module, learners will:

Understand the theoretical foundations and practical applications of Naïve Bayes and Decision Tree algorithms.
Gain proficiency in constructing, optimizing, and interpreting Decision Trees.
Apply Naïve Bayes classifiers effectively to solve classification problems.
Acquire hands-on experience through practical exercises to implement these algorithms in real-world scenarios.

Who is AI/ML: Naive Bayes and Decision Tree -Module 3 Course for?

Data Scientists: Seeking advanced knowledge in classification algorithms.

Machine Learning Engineers: Interested in mastering Naïve Bayes and Decision Tree techniques.

AI Developers: Looking to enhance their skills in algorithm implementation.

Professionals: Wanting to apply classification techniques effectively in AI and ML projects.

What are the prerequisites for AI/ML: Naive Bayes and Decision Tree -Module 3 Course?

Basic understanding of machine learning concepts and algorithms.

Familiarity with Python programming for implementing algorithms.

Knowledge of statistical concepts such as probability and data distributions.

Available Training Modes

Live Online Training

1 Days

Course Outline Expand All

Expand All

Naïve Bayes

Brief Summary of Algo

NB and Text Analytics

NB and quantitative data

Decision Tree

What is Decision Tree and why it is popular

Get the rules and insights easily from Decision Tree

Issues with Decision Tree

How to address them using advance algorithms like RF, and Boosting

AI Explainablilty and Interpretable models

Who is the instructor for this training?

The trainer for this AI/ML: Naive Bayes and Decision Tree -Module 3 Training has extensive experience in this domain, including years of experience training & mentoring professionals.

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