Deploying Agentic AI on Azure: An Overview of Building Enterprise-Ready Intelligent Agents
Author(s): Kyle knudson Originally published on Towards AI. Building Enterprise-Ready Intelligent Agents on Azure: A Practical Guide Agentic AI is quickly evolving from a buzzword into a core enterprise capability. We are moving past simple chatbots that just summarize text; today, we …
Mastering Extractive Summarization: A Theoretical and Practical Guide to TF-IDF and TextRank
Author(s): VARUN MISHRA Originally published on Towards AI. Mastering Extractive Summarization: A Theoretical and Practical Guide to TF-IDF and TextRank Text summarization is a cornerstone of natural language processing (NLP), enabling us to distill lengthy documents into concise summaries. Two popular extractive …
Understanding L1 and L2 Regularization in Machine Learning
Author(s): VARUN MISHRA Originally published on Towards AI. Understanding L1 and L2 Regularization in Machine Learning Regularization is a fundamental technique in machine learning used to prevent overfitting, improve model generalization, and ensure that models perform well on unseen data. Two of …
The Silent Revolution: How AI Browsers Are Quietly Rewriting the Rules of Human-Internet Interaction — And Why You’re Already Behind
Author(s): Riyas Raaz Originally published on Towards AI. In the quiet hours of October 2024, while most of the world slept through what seemed like just another tech announcement, something unprecedented happened. OpenAI didn’t just launch another chatbot feature. They released ChatGPT …
Why making Bigger LLMs Won’t Lead to AGI And What We’re Missing
Author(s): Sayan Chowdhury Originally published on Towards AI. Why making Bigger LLMs Won’t Lead to AGI And What We’re Missing Every few months, a new AI model is released that feels smarter, faster, and more capable than the last. Chatbots can write …
MCP Servers That Are Actually Useful
Author(s): Kushal Banda Originally published on Towards AI. Let’s explore Model Context Protocol (MCP) a powerful way to connect tools, data, and models. MCP lets you run servers that expose capabilities like search, file operations, or custom APIs, and make them instantly …
PyTorch: An Overview
Author(s): Rashmi Originally published on Towards AI. PyTorch: An Overview PyTorch is an open-source deep learning framework developed by Meta AI (formerly Facebook AI). It’s a Python-based library that provides tensor computation with GPU acceleration and a dynamic computational graph for building …
(p,d,q): The Understated Framework Behind Serious Forecasting
Author(s): VARUN MISHRA Originally published on Towards AI. (p,d,q): The Understated Framework Behind Serious Forecasting Forecasting is often treated as a technological problem — throw data into a model, tweak a few knobs, and wait for predictions to appear. The reality is …
XGBoost vs. Random Forest: A Sophisticated Analysis of Superiority in Real-World Data
Author(s): VARUN MISHRA Originally published on Towards AI. XGBoost vs. Random Forest: A Sophisticated Analysis of Superiority in Real-World Data In the pantheon of machine learning ensemble methods, Random Forest and XGBoost stand as titans, wielding tree-based architectures to conquer structured data …
Mastering Naive Bayes: Concepts, Math, and Python Code
Author(s): Jeet Mukherjee Originally published on Towards AI. You can never ignore Probability when it comes to learning Machine Learning. Naive Bayes is a Machine Learning algorithm that utilizes Bayes' theorem from probability theory as its foundation. It is primarily used for …
Quantum Neural Networks: Theoretical Heaven, Practical Hell
Author(s): David Such Originally published on Towards AI. Why Exponential Power Meets Exponential Pain in Quantum AI Development. The pursuit of artificial general intelligence has long relied on silicon chips and the classical mathematics of vast, interconnected neural networks. But as datasets …
Why Your Machine Learning Model Fails on Real Data: A Complete Guide to Ridge & Lasso
Author(s): AbhinayaPinreddy Originally published on Towards AI. The Mistake I Made Picture this: You’ve built a stock prediction model using 50 technical indicators. It looks perfect on your training data. You’re about to invest real money based on its predictions. Then you …
Why 73% of AI Agents Are Vulnerable to This “Invisible” Attack
Author(s): Adham Khaled Originally published on Towards AI. From Google Antigravity to Claude: How Indirect Prompt Injection turns helpful bots into data thieves. On November 18, Google launched Antigravity, a revolutionary “Agent-First IDE” designed to compete with tools like Cursor and Windsurf. …
Why the Future of GPU Architectures Will Redefine AI Strategy for Every Company
Author(s): Igor Voronin Originally published on Towards AI. Over the last few years, AI has moved faster than anyone expected. And the next chapter of AI isn’t being written in model papers or research labs. It’s being written inside the hardware that …
The Day Our Power BI Report Crashed the CEO’s Laptop
Author(s): Gulab Chand Tejwani Originally published on Towards AI. How a 2GB dataset, runaway DAX measures, and a security breach taught me everything about Power BI optimization The email arrived at 7:47 AM on a Monday. The Scene of the CrimeThe article …
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