K-means 2 | IREA

This course was created with the

course builder. Create your online course today. Start now

Create your course with

Autoplay
Autocomplete

Previous Lesson Complete and Continue

Artificial Intelligence

Artificial Intelligence for young people – AIM4YOU

Welcome to AIM4YOU 😊 - course trailer (1:00)
About this course
Promo video 2022 (6:14)

A gentle introduction

Prelude
Getting started
First thoughts (1:42)
Examples 1 (1:24)
Examples 2 (1:02)
Examples 3 (9:02)
Examples 4 (4:24)
AI hype (5:48)
AI definition (7:47)
The Turing test (8:42)
AI features and practice 1 (3:48)
AI features and practice 2 (5:49)
AI features and practice 3 (6:44)
To AI or not to AI (7:58)
Further readings

Core AI: representation and reasoning

Prelude
Cognitive psychology 1 (5:30)
Cognitive psychology 2 (5:12)
Cognitive psychology 3 (3:59)
Types of knowledge (2:32)
Search (5:18)
Intelligent agents (4:56)
Representation and reasoning 1 (5:05)
Representation and reasoning 2 (5:26)
Representation and reasoning 3 (1:51)
Quiz
Further readings

Machine learning

Prelude
Introduction to machine learning (5:40)
Matrices and vectors 1 (4:53)
Matrices and vectors 2 (4:12)
Eigenvalues and eigenvectors (6:52)
Principal component analysis (7:51)
Machine learning as a prediction engine (1:41)
Common learning mechanisms (2:15)
Introduction to supervised machine learning algorithms (2:51)
Linear regression (2:41)
Naive Bayes (2:40)
Support vector machines (2:13)
K-nearest neighbors (1:50)
Decision tree (3:57)
Random forest (1:37)
Introduction to unsupervised machine learning algorithms (2:06)
K-means 1 (4:46)
K-means 2 (2:20)
DB-scan (6:19)
Hierarchical clustering (1:04)
Quiz
Further readings

Neural networks

Prelude
Neuron as a function (2:29)
Types of neural networks (1:27)
Single-layer perceptron (2:08)
Multi-layer perceptron (1:36)
Radial basis function (2:01)
Self-organizing map (3:19)
Extreme learning machine (2:09)
Loss functions (1:33)
Learning algorithms (3:33)
Gradient descent (4:03)
Problems with SGD and their solutions (5:40)
Problems during construction and training of neural networks (3:54)
Vanishing and exploding gradients (6:01)
Overfitting and underfitting (4:19)
Convolutional neural networks (5:29)
Various CNN architectures (4:34)
Recurrent neural networks (6:52)
Long short-term memory (4:29)
Autoencoders (4:55)
Generative adversarial network (5:42)
Quiz
Further readings

Natural language processing

Prelude
Introduction to NLP (5:25)
NLP foundations (11:38)
Language modelling (5:35)
Parsing (8:25)
Semantics (4:27)
Word2vec (4:21)
Contextual word embedding (4:37)
Classification tasks in NLP (6:42)
Sentiment analysis (5:42)
Text/document clustering with K-means (6:22)
Topic modeling 1 (3:58)
Topic modeling 2 (3:14)
Topic modeling 3 (4:30)
Quiz
Further readings

Real-world applications

Prelude
AI home assistants (4:36)
Self-driving cars (4:41)
Black lives matter (4:47)
Robotics 1 (5:02)
Robotics 2 (1:51)
Robotics 3 (2:39)
Robotics 4 (1:45)
Robotics 5 (1:00)
Solar concentrator (1:22)
Further readings

Review. Ethics and personalization in AI

Prelude
Review 1 (7:31)
Review 2 (4:07)
Personalization 1 (5:14)
Personalization 2 (5:23)
Ethics 1 (2:27)
Ethics 2 (3:51)
Quiz
Further readings

K-means 2

Complete and Continue