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…
Deep Learning (DL) is a subset of Machine Learning (ML), which itself is a subset of Artificial Intelligence (AI). They share similarities but differ in complexity, data requirements, and applications. 1. How…
What is Machine Learning? Machine Learning (ML) is a branch of Artificial Intelligence (AI) that enables computers to learn from data and improve their performance without being explicitly programmed. Instead of following fixed rules, ML…
