Artificial Intelligence & Machine Learning Course
What is Artificial Intelligence?
Artificial Intelligence (AI) is a branch of computer science that focuses on creating machines capable of performing tasks that normally require human intelligence.
Examples of AI applications include voice assistants, recommendation systems, self-driving cars, fraud detection, and chatbots.
What is Machine Learning?
Machine Learning (ML) is a subset of Artificial Intelligence that enables systems to automatically learn from data and improve performance without being explicitly programmed.
Instead of writing rules manually, machine learning models identify patterns in data.
AI vs Machine Learning vs Deep Learning
| Technology | Description |
|---|---|
| Artificial Intelligence | Broad concept of machines performing intelligent tasks. |
| Machine Learning | Subset of AI that learns patterns from data. |
| Deep Learning | Advanced ML using neural networks with many layers. |
Python for Artificial Intelligence
Python is the most popular programming language for AI and machine learning because of its simplicity and powerful libraries.
Common AI libraries in Python include:
- NumPy
- Pandas
- Scikit-learn
- TensorFlow
- PyTorch
NumPy Basics
NumPy is a Python library used for numerical computing and handling arrays.
import numpy as np
arr = np.array([1,2,3,4])
print(arr)
Pandas for Data Analysis
Pandas is used to manipulate and analyze structured data such as CSV files, Excel files, and databases.
import pandas as pd
data = pd.read_csv("data.csv")
print(data.head())
Supervised Learning
Supervised learning is a type of machine learning where the model is trained using labeled data.
Examples include:
- Email spam detection
- House price prediction
- Image classification
Unsupervised Learning
Unsupervised learning works with data that does not have labeled outputs.
The algorithm tries to discover hidden patterns in the data.
Examples:- Customer segmentation
- Market basket analysis
Common Machine Learning Algorithms
- Linear Regression
- Logistic Regression
- Decision Tree
- Random Forest
- K-Nearest Neighbors
- Support Vector Machine
AI Chatbot
AI chatbots use Natural Language Processing (NLP) to understand user input and respond intelligently.
Examples include customer support bots and virtual assistants.Recommendation System
Recommendation systems suggest products, movies, or content to users based on their preferences.
Examples:- Amazon product recommendations
- Netflix movie suggestions
- YouTube video recommendations
Image Recognition
Image recognition uses deep learning models to identify objects inside images.
Examples:- Face recognition
- Medical image diagnosis
- Self-driving car vision systems