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Machine learning with Python fundermentals

3 Units13 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 3•Chapter 5

Real-World Project: Training an Agent for Autonomous Robot Navigation

Summary

Provide a summary of the transcript that is no more than 250 words, focuses solely on the main topic, and omits any introductory statements

Concept Check

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In autonomous robot navigation, what technique balances exploration and exploitation in reinforcement learning?

What role does Q-learning play in training navigation agents?

How does LiDAR contribute to robot navigation training?

What is a key challenge in state representation for navigation agents?

Which algorithm is ideal for partially observable environments in navigation?

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