Imagine you're teaching a child to tell the difference between cats and dogs. You don't give them a rigid rulebook. Instead, you show them hundreds of pictures, pointing out features…
1. Linear Models These models assume that the classes can be separated by a linear decision boundary (a straight line or a flat plane). Logistic Regression: What it is: Despite its…
Python is the most popular language for machine learning (ML) and data science due to its simplicity, versatility, and a rich ecosystem of libraries. Here’s why Python dominates ML1. Easy to Learn & Read…
Scikit-learn (also called sklearn) is a free, open-source Python library for machine learning. It provides simple and efficient tools for: Supervised Learning (classification, regression) Unsupervised Learning (clustering, dimensionality reduction) Model evaluation (cross-validation, metrics) Data preprocessing (scaling, feature extraction)…
1. High-Level ML Workflow Diagram A typical ML pipeline can be visualized as a cyclic process with the following stages: [Data Collection] → [Data Preprocessing] → [Feature Engineering] → [Model Training] →…
1. Example: Sentiment Analysis AI (Text Classification) Goal: Train an ML model to classify movie reviews as positive or negative. 2. Step-by-Step Implementation 1. Install Required Libraries bash pip install pandas scikit-learn nltk…
Choose an AI Type TypeDescriptionExampleRule-Based AIFollows predefined if-else rulesChatbot, Decision TreeMachine Learning (ML) AILearns from dataImage classifier, Spam detectorChatbot (NLP)Uses natural language processingCustomer support bot 1. Build a Simple Rule-Based…
