Technical Explorations

Field Notes

POST-01
10 min read

Agentic AI: Complete Guide to AI Agents in 2025

Discover how agentic AI is transforming automation in 2025. Learn what AI agents are, how they work, and how to build your own autonomous systems.

Agentic AIAI AgentsLLM+2
POST-02
8 min read

Context Engineering: The New Frontier for AI Teams in 2025

Why AI teams are shifting from prompt to context engineering—and how to master this discipline for better LLM performance.

Context EngineeringAIData Science+2
POST-03
10 min read

Explainable AI and Ethics: Complete Guide 2025

Master Explainable AI (XAI): SHAP and LIME techniques, European regulation, and responsible models. A practical guide for developers.

Explainable AIXAIAI Ethics+2
POST-04
9 min read

Small Language Models vs LLMs: Complete Guide 2025

Discover why Small Language Models are revolutionizing AI: faster, cheaper, and local without sacrificing quality. A practical guide for 2025.

SLMLLMArtificial Intelligence+2
POST-05
8 min read

Getting Started with RAG: A Practical Guide

Learn how to build your first Retrieval-Augmented Generation system from scratch, with practical examples and best practices.

RAGLLMPython+1
POST-06
10 min read

PCA: Dimensionality Reduction Explained

Master PCA for dimensionality reduction. Learn the math, Python implementation, and when to use it in your ML projects.

Machine LearningPCADimensionality Reduction+1
POST-07
9 min read

K-Means Clustering: Grouping Data Without Labels

Master K-Means clustering to discover hidden patterns in your data. Learn the algorithm, Python implementation, and real-world applications.

Machine LearningClusteringK-Means+1
POST-08
8 min read

K-Nearest Neighbors: The Simplest ML Algorithm

Master KNN algorithm from scratch. Learn distance metrics, choosing K, Python implementation, and when to use this intuitive classifier.

Machine LearningKNNClassification+1
POST-09
10 min read

Random Forests: Ensemble Learning for Better Predictions

Master Random Forests: learn how ensemble learning combines multiple decision trees for robust, accurate predictions in Python.

Machine LearningRandom ForestEnsemble Learning+1
POST-10
9 min read

Decision Trees: How Machines Make Decisions Like Humans

Learn how decision trees work, from entropy to pruning, with Python examples and visualizations.

Machine LearningDecision TreesClassification+1
POST-11
10 min read

Logistic Regression Demystified: Classification Made Simple

Master logistic regression for binary and multiclass classification with Python. From sigmoid function to sklearn implementation.

Machine LearningLogistic RegressionClassification+1
POST-12
12 min read

Linear Regression from Scratch: Math, Code, and Intuition

Master linear regression by building it from scratch. Learn the math, implement with NumPy, and visualize results step by step.

Machine LearningLinear RegressionPython+1
POST-13
8 min read

Supervised vs Unsupervised Learning: When to Use Each

Master the key differences between supervised and unsupervised learning to choose the right approach for your ML projects.

Machine LearningSupervised LearningUnsupervised Learning+1
POST-14
10 min read

The Machine Learning Workflow: From Data to Deployment

Master the complete ML pipeline from raw data to production-ready models with practical Python examples and best practices.

Machine LearningMLOpsData Science+1
POST-15
8 min read

What is Machine Learning? A Complete Beginner's Guide

Discover what Machine Learning is, how it works, and start coding your first ML model with Python in this practical guide.

Machine LearningAIBeginners+1