Weekly AI Knowledge Sharing

A High-Level Roadmap to Start Learning AI in 2026 If you’re planning to learn AI in 2026, here’s the good news:You don’t need to know everything.You just need a structured direction. After meeting developers, leaders, and beginners over the years, I’ve realized one thing…

Spam Email Detection Using Classification Algorithms Every day, billions of emails are sent worldwide — and a shocking percentage of them are spam. From fake offers to phishing scams, spam not only clutters inboxes but can also compromise security.That’s where Machine Learning steps in…

Topic: LangGraph – Building Agentic AI Workflows with Graph-Based Frameworks If you’re exploring the next frontier of AI — beyond one-shot prompts and simple chains — here’s why LangGraph matters. 🔍 What is LangGraph? LangGraph is a framework designed for building multi-agent, stateful AI…

Building a Machine Learning (ML) model may sound complex, but the journey can be broken into three core stages: 🔹 1. Create (Data Preparation & Model Selection) 🔹 2. Train (Model Training & Evaluation) 🔹 3. Deploy (Operationalize Your Model) 💡 Beginner Project Ideas…

When working with AI, most people focus on “natural” instructions. But here’s a secret weapon: Regular Expressions (Regex) inside prompts. 👉 Regex isn’t just for programmers. It’s a powerful way to control AI outputs with precision. Why Use Regex in Prompts? 1️⃣ Structured Outputs…

Databricks for Analytics: Where to Start & What to Learn Databricks has quickly become the go-to platform for data engineering, analytics, and AI. It unifies data storage, processing, and machine learning into one ecosystem — making it an essential skill if you want to…