Introduction to AI and ML

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69 pages
Law
akhz
69 pages
Law
107
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GNEST305
INTRODUCTION TO ARTIFICIAL INTELLIGENCE
AND DATA SCIENCE
Module 1
Introduction to AI and Machine learning: Basics of Machine Learning- types of
machine learning systems – challenges in ML – supervised learning model example
– regression models – classification model example- logistic regression –
unsupervised model example- K-means clustering.
Artificial Neural Network- Perceptron- Universal Approximation Theorem
(statement only)- Multi-Layer Perceptron- Deep Neural Network- demonstration of
regression and classification problems using MLP.
Ktu-notes-2024.web.app
Ktu-notes-2024.web.app
What is Artificial Intelligence?
• Artificial Intelligence(AI) is that branch of computer science that creates intelligent
machines that think and act like humans.
• AI enables machines to think, learn and adapt, to enhance and automate tasks across
industries.
• A few examples of AI are ChatGPT, Google Translate, and many more.
The Venn Diagram of AI, ML and DL
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Figures

M1 INTRODUCTION TO AI EC DEPARTMENT — The Venn Diagram of AI, ML and DL
M1 INTRODUCTION TO AI EC DEPARTMENT — What Is Machine Learning?
Since the problem is difficult, your program
M1 INTRODUCTION TO AI EC DEPARTMENT — Why Use Machine Learning?
M1 INTRODUCTION TO AI EC DEPARTMENT — Types of Machine Learning Systems
M1 INTRODUCTION TO AI EC DEPARTMENT — Supervised learning
M1 INTRODUCTION TO AI EC DEPARTMENT — Classification
M1 INTRODUCTION TO AI EC DEPARTMENT — Unsupervised learning
M1 INTRODUCTION TO AI EC DEPARTMENT — Clustering
M1 INTRODUCTION TO AI EC DEPARTMENT — Association
Environment-Agent loop
M1 INTRODUCTION TO AI EC DEPARTMENT — The
Step 2: Plot WCSS vs. K
M1 INTRODUCTION TO AI EC DEPARTMENT — Step 3: Find the "Elbow“:
M1 INTRODUCTION TO AI EC DEPARTMENT — Logistic Regression
M1 INTRODUCTION TO AI EC DEPARTMENT — Figure 16
M1 INTRODUCTION TO AI EC DEPARTMENT — Introduction to Artificial Neural Networks (ANNs)
M1 INTRODUCTION TO AI EC DEPARTMENT — c) Output Layer
M1 INTRODUCTION TO AI EC DEPARTMENT — Structure of a Perceptron
Architecture of a Multilayer Perceptron with two inputs, one hidden layer of four neurons, and three output neurons
M1 INTRODUCTION TO AI EC DEPARTMENT — Hidden layer calculations:
M1 INTRODUCTION TO AI EC DEPARTMENT — Hidden layer calculations:
A modern MLP (including ReLU and softmax) for classification
If the input is
M1 INTRODUCTION TO AI EC DEPARTMENT — Universal Approximation Theorem (UAT)

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