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Machine learning with Python fundermentals
3 Units
13 Lessons
Unit 1
Supervised Learning
Introduction to Supervised Learning Concepts
Regression Techniques in Supervised Learning
Classification Algorithms for Supervised Models
Real-World Project: Building a Predictive Model for Medical Diagnosis
Unit 2
Unsupervised Learning
Introduction to Unsupervised Learning Principles
Clustering Methods in Unsupervised Learning
Dimensionality Reduction Techniques
Real-World Project: Customer Segmentation Using Unsupervised Methods
Unit 3
Reinforcement Learning
Fundamentals of Reinforcement Learning
Markov Decision Processes in Reinforcement Learning
Q-Learning and Value-Based Methods
Policy Gradient Methods in Reinforcement Learning
Real-World Project: Training an Agent for Autonomous Robot Navigation
Unit 2
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Chapter 1
Introduction to Unsupervised Learning Principles
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What is the primary difference between K-means and DBSCAN in unsupervised learning?
K-means is density-based.
DBSCAN handles arbitrary shapes better.
K-means requires predefined cluster count.
K-means requires predefined cluster count.
In unsupervised learning, what does PCA primarily achieve?
Reduces data dimensionality while retaining variance.
Reduces data dimensionality while retaining variance.
Increases feature correlations.
Classifies data points accurately.
How does the curse of dimensionality affect unsupervised learning?
Data becomes sparse in high-dimensional spaces.
Improves clustering efficiency.
Data becomes sparse in high-dimensional spaces.
Reduces computational needs.
What role does silhouette score play in unsupervised learning evaluation?
Predicts future data patterns.
Measures cluster quality based on cohesion and separation.
Calculates data labels automatically.
Measures cluster quality based on cohesion and separation.
In unsupervised learning, what is the main goal of association rule learning?
Reduces noise in data.
Classifies data into categories.
Finds interesting relationships in large datasets.
Finds interesting relationships in large datasets.
5 questions remaining
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Clustering Methods in Unsupervised Learning