Artificial Intelligence for young people – AIM4YOU
A gentle introduction
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Prelude
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Getting started
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First thoughts (1:42)
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Examples 1 (1:24)
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Examples 2 (1:02)
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Examples 3 (9:02)
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Examples 4 (4:24)
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AI hype (5:48)
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AI definition (7:47)
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The Turing test (8:42)
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AI features and practice 1 (3:48)
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AI features and practice 2 (5:49)
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AI features and practice 3 (6:44)
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To AI or not to AI (7:58)
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Further readings
Core AI: representation and reasoning
Machine learning
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Prelude
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Introduction to machine learning (5:40)
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Matrices and vectors 1 (4:53)
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Matrices and vectors 2 (4:12)
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Eigenvalues and eigenvectors (6:52)
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Principal component analysis (7:51)
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Machine learning as a prediction engine (1:41)
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Common learning mechanisms (2:15)
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Introduction to supervised machine learning algorithms (2:51)
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Linear regression (2:41)
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Naive Bayes (2:40)
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Support vector machines (2:13)
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K-nearest neighbors (1:50)
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Decision tree (3:57)
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Random forest (1:37)
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Introduction to unsupervised machine learning algorithms (2:06)
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K-means 1 (4:46)
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K-means 2 (2:20)
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DB-scan (6:19)
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Hierarchical clustering (1:04)
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Quiz
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Further readings
Neural networks
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Prelude
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Neuron as a function (2:29)
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Types of neural networks (1:27)
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Single-layer perceptron (2:08)
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Multi-layer perceptron (1:36)
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Radial basis function (2:01)
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Self-organizing map (3:19)
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Extreme learning machine (2:09)
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Loss functions (1:33)
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Learning algorithms (3:33)
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Gradient descent (4:03)
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Problems with SGD and their solutions (5:40)
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Problems during construction and training of neural networks (3:54)
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Vanishing and exploding gradients (6:01)
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Overfitting and underfitting (4:19)
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Convolutional neural networks (5:29)
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Various CNN architectures (4:34)
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Recurrent neural networks (6:52)
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Long short-term memory (4:29)
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Autoencoders (4:55)
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Generative adversarial network (5:42)
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Quiz
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Further readings
Natural language processing
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Prelude
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Introduction to NLP (5:25)
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NLP foundations (11:38)
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Language modelling (5:35)
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Parsing (8:25)
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Semantics (4:27)
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Word2vec (4:21)
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Contextual word embedding (4:37)
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Classification tasks in NLP (6:42)
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Sentiment analysis (5:42)
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Text/document clustering with K-means (6:22)
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Topic modeling 1 (3:58)
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Topic modeling 2 (3:14)
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Topic modeling 3 (4:30)
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Quiz
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Further readings
Real-world applications
Review. Ethics and personalization in AI
