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Machine Learning with Python Training (beginner to advanced)

Deep dive into Machine Learning with Python Programming. Implement practical scenarios & a project on Recommender System
2,483 Students enrolled
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Machine Learning with Python – Course Syllabus

1. Introduction to Machine Learning

  • What is Machine Learning?

  • Need for Machine Learning

  • Why & When to Make Machines Learn?

  • Challenges in Machines Learning

  • Application of Machine Learning

2. Types of Machine Learning

  • Types of Machine Learning

       a) Supervised learning

       b) Unsupervised learning

       c) Reinforcement learning

  • Difference between Supervised and Unsupervised learning

  • Summary

3. Components of Python ML Ecosystem

  • Using Pre-packaged Python Distribution: Anaconda

  • Jupyter Notebook

  • NumPy

  • Pandas

  • Scikit-learn

4. Regression Analysis (Part-I)

  • Regression Analysis

  • Linear Regression

  • Examples on Linear Regression

  • scikit-learn library to implement simple linear regression

5. Regression Analysis (Part-II)

  • Multiple Linear Regression

  • Examples on Multiple Linear Regression

  • Polynomial Regression

  • Examples on Polynomial Regression

6. Classification (Part-I)

  • What is Classification

  • Classification Terminologies in Machine Learning

  • Types of Learner in Classification

  • Logistic Regression

  • Example on Logistic Regression

7. Classification (Part-II)

  • What is KNN?

  • How does the KNN algorithm work?

  • How do you decide the number of neighbors in KNN?

  • Implementation of KNN classifier

  • What is a Decision Tree?

  • Implementation of Decision Tree

  • SVM and its implementation

8. Clustering (Part-I)

  • What is Clustering?

  • Applications of Clustering

  • Clustering Algorithms

  • K-Means Clustering

  • How does K-Means Clustering work?

  • K-Means Clustering algorithm example

9. Clustering (Part-II)

  • Hierarchical Clustering

  • Agglomerative Hierarchical clustering and how does it work

  • Woking of Dendrogram in Hierarchical clustering

  • Implementation of Agglomerative Hierarchical Clustering

10. Association Rule Learning

  • Association Rule Learning

  • Apriori algorithm

  • Working of Apriori algorithm

  • Implementation of Apriori algorithm

11. Recommender Systems

  • Introduction to Recommender Systems

  • Content-based Filtering

  • How Content-based Filtering work

  • Collaborative Filtering

  • Implementation of Movie Recommender System

How long do I have access to the course materials?
You can view and review the lecture materials indefinitely, like an on-demand channel.
Can I take my courses with me wherever I go?
Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don't have an internet connection, some instructors also let their students download course lectures. That's up to the instructor though, so make sure you get on their good side!
Course details
Lectures 12
Quizzes 3
Video 24 hours
Certificate of Completion
Full lifetime access
Access on mobile and TV

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