Articles | Notes | Tips | Tutorials
In this primer, we will provide an overview of the the emerging standard Model Context Protocol (or MCP) specification for building Agentic LLM apps AND get our hands dirty with some code samples using Ollama and LangChain.
Here is the link to the article on MCP:
Quick Primer on Model Context Protocol (MCP)
Enjoy 🙂 !!!
In this primer, we will provide an overview of the popular Python open source asynchronous web framework called Starlette and get our hands dirty by building some simple web backends.
Here is the link to the article on Starlette:
Enjoy 🙂 !!!
In this article, we will provide code snippets for commonly performed tasks using the popular LLM framework LangChain.
Here is the link to the article on common LangChain recipes:
Enjoy 🙂 !!!
In this next part of the Deep Learning series, we will explain how a Convolutional Neural Network (CNN) model works and use PyTorch for a practical demonstration to classify images of digits using the MNIST dataset.
Here is the link to the article on Deep Learning using CNN:
Deep Learning – Convolutional Neural Network
Enjoy 🙂 !!!
In this primer, we will provide an overview of the popular Agentic framework built on top of LangChain called the LangGraph AND get our hands dirty with some code samples on the various use-cases.
Here is the link to the article on LangGraph:
Enjoy 🙂 !!!
For the users of JetBrains DataSpell IDE for all AI/ML notebook work, if the Markdown appears blank, try the following steps to fix:
Hope this tip helps others looking for a solution !!!
In this short quick tip article, we will demonstrate how one can run the ‘Flux.1-Schnell‘ text-to-image Diffusion model on a local machine (either a desktop with 16gb NVidia GPU or an Apple Silicon Mac) to generate an image given an input prompt.
Here is the link to the short quick tip article:
Quick Tip :: Running Text-to-Image Diffusion Model on a Local Machine
P.S: This is the 400th article post on PolarSPARC !!!
Happy New Year – Enjoy 🙂 !!!
In Part-3 of this primer series, we will enhance the custom Rasa helper chatbot such that, it is configured, trained, and deployed once, to leverage data from an external source for future knowledge expansion.
Here is the link to the article on enhanced Rasa custom helper chatbot:
Hands-on Primer on Rasa – Part 3
Enjoy 🙂 !!!
Most of us have been using some form of a badge or tag to enter the office building OR tap a credit card to make a payment at the checkout.
Ever wondered what is really going on behind the scene when we tap a card on the card reader ???
This is where the RFID/NFC technology comes into play. We will leverage a Raspberry Pi 4 along with a Mifare RC522 RFID module to get our hands dirty. Here is the link to the article demonstrating the concept of RFID/NFC:
Enjoy 🙂 !!!
In this article, we will understand the basics of model Quantization which allows one to shrink the size of any pre-trained LLM model.
Here is the link to the article on Quantization:
Understanding Model Quantization
Enjoy 🙂 !!!