Author: Naveen

Naveen Pandey has more than 2 years of experience in data science and machine learning. He is an experienced Machine Learning Engineer with a strong background in data analysis, natural language processing, and machine learning. Holding a Bachelor of Science in Information Technology from Sikkim Manipal University, he excels in leveraging cutting-edge technologies such as Large Language Models (LLMs), TensorFlow, PyTorch, and Hugging Face to develop innovative solutions.

Naveen Pandey
May 31, 2026May 31, 2026

Build an AI Agent with Real Memory Using Mem0, LangChain, and Groq

Most AI agents are very forgetful. You can introduce yourself, tell them about your project, your preferences, and your goals — but when it’s time to interact again, it’s gone. This is because most chatbots only have short-term memory, rather than long-term memory. It is one of the most significant constraints of the contemporary AI…

Naveen Pandey
May 24, 2026May 24, 2026

Build a Multimodal RAG System That Understands PDFs (Text + Images) Using Groq

The majority of RAG systems nowadays are not complete, they read the text but not the images, which actually describe the information. When your system is not able to retrieve diagrams, charts, and images of documents, it lacks half the knowledge. This is one of the most prevalent gaps according to the experience of building…

Naveen Pandey
May 9, 2026May 9, 2026

From RAG to Agentic AI: Building a Multi-Agent Multimodal RAG System with Text, Diagrams, and Images

Traditional RAG systems retrieve information. Modern AI systems decide how to respond. That shift—from retrieval to reasoning—is what defines the next generation of intelligent systems. In this article, we build a Multi-Agent Multimodal RAG system that not only retrieves knowledge but also decides whether to respond with text, generate a structured diagram, or produce a…

Naveen Pandey
April 4, 2026April 4, 2026

Generative AI vs Agentic AI: What’s the Real Difference?

Generative AI is used to create, whereas Agentic AI is used to finish. Generative AI is sufficient, in case you are just in need of text, code, or images. However, when you want to automatize procedures, make decisions and conduct multi-step processes, the appropriate solution is Agentic AI. This difference is made apparent in a…

Naveen Pandey
March 21, 2026March 21, 2026

Agentic AI: The Rise of Autonomous AI Agents and Multi-Agent Systems

The development of Artificial Intelligence has occurred in a series of steps over the last ten years. The initial AI systems were mostly rule-based and were only able to execute the tasks which had to be programmed by programmers. The machine learning models allowed systems to learn patterns on the basis of data later, and…

Naveen Pandey
February 8, 2026February 8, 2026

Context Engineering: The Secret Behind Every AI Conversation

Every time you chat with an AI like ChatGPT or Claude, something fascinating happens behind the scenes—it completely forgets you the moment the conversation ends. Sounds harsh, right? But here’s the thing: this isn’t a bug, it’s just how these systems work. So how do they manage to keep a conversation going when you send…

Naveen Pandey
November 15, 2025November 15, 2025

Top 5 Skills Every Engineer Should Learn in 2026

The world of engineering is changing faster than ever before. Technologies that were once futuristic like artificial intelligence, machine learning, and cloud computing are now driving industries forward. By 2026, the engineers who thrive won’t just be the one who can code or design systems. They will be the one who can adapt, analyze, automate…

Naveen Pandey
July 6, 2025November 9, 2025

Zero to Python Hero - Part 3/10 : Understanding Type Casting, Operators, User Input and String formatting (with Code Examples)

Type Casting & Checking What is Type Casting? Type casting (also called type conversion) is the process of converting a value from one data type to another. It’s like translating between different languages – sometimes you need to convert a number to text, or text to a number, so different parts of your program can work together.…

Naveen Pandey
June 28, 2025November 9, 2025

Zero to Python Hero - Part 2/10 : Understanding Python Variables, Data Types (with Code Examples)

Learning Python can feel overwhelming when you’re starting from scratch. I discovered this firsthand while researching about the Python resources online. As I went through countless tutorials, documentation pages, and coding platforms, I realized a frustrating truth: beginners often have to jump between multiple websites, books, and resources just to understand the basics. Even worse,…

Naveen Pandey
April 26, 2025November 8, 2025

Ridge Regression for Beginners

In this article, we will cover the basics of Ridge regression. The main advantage of Ridge regression is to avoid overfitting. The ultimate goal is to obtain a regression model that can generalize patterns and perform well on both the training and testing data. We want to avoid a model that overfits the data, meaning…

Naveen Pandey
April 21, 2025November 8, 2025

A Comprehensive Guide to the RBF Kernel in Machine Learning

Kernel methods are a powerful set of machine learning algorithms that can be used to solve both classification and regression problems. Kernel methods work by transforming the input data into a higher-dimensional space, where it is easier to find linear relationships between the data points. This transformation is performed using a kernel function, which is…

Naveen Pandey
April 20, 2025November 8, 2025

Fine-Tuning BERT for 90%+ Accuracy in Text Classification

What are Pretrained Language Models? Pretrained Language Models (PLMs) are deep learning models trained on large corpus of text to understand the structure and nuances of natural language. These models are used as a foundation for various Natural Language Processing (NLP) tasks, including Fine tuning BERT for text classification, significantly improving performance compared to training from…