Data Cleaning & Wrangling – From Raw Mess to ML-Ready Data
Explore the essential techniques to clean, transform, and structure raw data before feeding it into machine learning models.
AI explanations that actually explain.
Complex ideas are transformed into clear explanations, supported by visuals and guides that make artificial intelligence accessible to everyone.
The NovamAI Journal
Overview of the End-to-End Machine Learning Engineering Workflow
Learn the four pipelines with a practical tour of the end-to-end ML workflow (from data to models to deployment).
Agentic AI vs. Agents AI : the Future of Autonomous Systems
A clear breakdown of the differences and overlaps between agentic AI and software agents, highlighting their behaviors, architectures, and implications for developers building autonomous systems.
Understanding AI Agents: Types, Behaviors, and Frameworks Explained
AI agents are intelligent systems designed to autonomously perform tasks, make decisions, or provide insights based on their programmed goals. These agents can operate independently or collaboratively, depending on their design, and are widely used in domains ranging from customer support to autonomous vehicles.
Tokenization - Comprehensive Guide
Tokenization is a foundational step in Natural Language Processing (NLP). Whether you’re building a sentiment analysis model, a text classifier, or a large language model (LLM) like GPT, understanding tokenization is essential.
DAPO - 4 Optimization Techniques to Enhance AI Mathematical Reasoning
Ever wondered how ChatGPT solves complex problems? Some researchers just released DAPO, an open-source method that’s outperforming the secret sauce from companies like OpenAI and DeepSeek. Let’s break it down
