Course summary
Session Start 13/11/2024
Location Online
Duration 4h 22m
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U1: Introduction
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Presentation
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influences
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U2: The basics of machine learning
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What is machine learning?
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Machine learning possibilities
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Configuration of the work environment
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U3: your first models
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Types and examples of machine learning
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Data: the basis of any model
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Python libraries
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Your first model: linear regression
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Linear regression in detail
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U4: Machine learning algorithms
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Sets and data analysis
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Linear regression exercise
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Logistic regression
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Logistic regression exercise
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decision trees
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Decision trees exercise
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U5: More machine learning algorithms
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support vector machines
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Support vector machine exercise
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Clustering with K-means
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Clustering exercise with K-means
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U6: Neural networks and deep learning
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Intuition and how neural networks learn
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Regression neural network
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Classification 1 neural network
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Classification Neural Network 2
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Convolutions and filters
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Convolutional Neural Networks 1
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Convolutional Neural Networks 2
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Learning Transfer 1
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Learning transfer 2
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Final project
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Introduction to AI with Python
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