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Machine Learning - Beginner Course
Chapter 1:
Machine Learning for Beginners
1
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1
Machine Learning Course for Absolute Beginners
Chapter 2:
Module 1:
Introduction to Machine Learning
3
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1
What is Machine Learning and How it Works (Beginner Guide)
2
Types of Machine Learning: Supervised, Unsupervised, and Reinforcement Learning
3
Real-Life Examples of Machine Learning: Recommendation Systems, Spam Filters, Chatbots
Chapter 3:
Module 3:
Data Preprocessing
5
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1
Machine Learning – Loading Datasets in Python (CSV, Excel, Built-in, and URLs)
2
Handling Missing Values and Outliers in Machine Learning
3
Encoding Categorical Data in Machine Learning (Beginner-Friendly Guide)
4
Machine Learning - Feature Scaling and Normalization
5
Train-Test Split in Machine Learning (With Examples and Python Code)
Chapter 4:
Module 4:
Supervised Learning
5
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1
Machine Learning - Linear Regression for Beginners
2
Machine Learning - Logistic Regression
3
Machine Learning - K-Nearest Neighbors (KNN)
4
Machine Learning - Decision Trees and Random Forest
5
Model Evaluation Metrics in Machine Learning (with Examples & Python Code)
Chapter 5:
Module 5:
Unsupervised Learning
3
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1
K-Means Clustering in Machine Learning: Explained with Examples and Python Code
2
Hierarchical Clustering in Machine Learning
3
Dimensionality Reduction with PCA in Machine Learning
Chapter 6:
Module 6:
Improving Models
4
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1
Cross-Validation Techniques in Machine Learning (With Examples)
2
Hyperparameter Tuning in Machine Learning
3
Understanding Overfitting vs Underfitting in Machine Learning
4
Bias-Variance Tradeoff in Machine Learning (with Python Examples)
Chapter 7:
Module 7:
Real-World Projects
4
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1
Titanic Survival Prediction Using Machine Learning
2
House Price Prediction Using Machine Learning (Step-by-Step Tutorial for Beginners)
3
Customer Segmentation Using Clustering - Machine Learning Project for Beginners
4
Email Spam Detection using Machine Learning
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