About Course
Machine learning is a branch of artificial intelligence (AI) that allows computers to learn from data and make decisions or predictions without explicit programming. By using algorithms to identify patterns in data, machine learning models improve over time, becoming more accurate as they process more information. This technology powers everything from recommendation systems on streaming platforms to advanced medical diagnostics, making it a cornerstone of modern AI applications.
Course Content
Introduction to Machine Learning and Data Preprocessing
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1.1 Understanding Machine Learning
01:25:00 -
Types of machine learning: Supervised, Unsupervised, and Reinforcement Learning
04:00:00 -
1.2 Real-World Applications
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1.3 Python and Java for Machine Learning
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Setting up the development environment for both languages
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1.4 Data Preprocessing Techniques
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Handling missing data: Techniques in Python (Pandas, NumPy) and Java (Weka)
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Data encoding: Label encoding and one-hot encoding
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Feature scaling: Standardization and normalization methods
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Splitting data into training and testing sets
Module 2: Core Machine Learning Algorithms
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