Machine Learning for Beginners
This course is designed for beginners with no prior experience in machine learning. It covers the fundamentals of machine learning and provides a solid foundation for further study. Students will learn basic machine learning algorithms, data preprocessing, and model evaluation.
What Will I Learn?
- What is machine learning?
- Types of machine learning algorithms
- Data preprocessing techniques
- How to build a regression model
- How to build a classification model
- How to perform cluster analysis
- How to evaluate machine learning models
- How to apply machine learning in real-world scenarios
- How to avoid common pitfalls in machine learning
- How to continue learning machine learning
Course Curriculum
Introduction to Machine Learning
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What is Machine Learning?
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Types of Machine Learning Algorithms
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Real-World Applications of Machine Learning
Data Preprocessing
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Introduction to Data Preprocessing
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Data Cleaning Techniques
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Data Transformation Techniques
Regression Analysis
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Introduction to Regression Analysis
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Linear Regression
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Multiple Linear Regression
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Polynomial Regression
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Evaluating Regression Models
Classification Analysis
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Introduction to Classification Analysis
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Logistic Regression
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Decision Trees
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Random Forests
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Evaluating Classification Models
Clustering Analysis
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Introduction to Clustering Analysis
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K-Means Clustering
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Hierarchical Clustering
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DBSCAN Clustering
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Evaluating Clustering Models