Articles | Notes | Tips | Tutorials
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 🙂 !!!
Posted my next article on LinkedIn and here is the link:
Hope is useful for others !!!
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 primer, we will provide an overview of the Ollama platform as well as get our hands dirty using the command-line as well as the Open WebUI.
Here is the link to the article on Ollama:
Enjoy 🙂 !!!
In this article, we will demonstrate how one can extend the business logic of a Java application, at runtime, by dynamically compiling and loading the class bytecode using the Java Compiler API.
Here is the link to the article on how one can use the Java Compiler API for dynamic code generation:
Dynamic Code Generation using Java Compiler API
Enjoy 🙂 !!!
This article demonstrates how one can externalize business logic in JavaScript and use the Nashorn engine to execute that business logic at runtime.
Here is the link to the article introducing Scripting in Java:
Introduction to Scripting In Java
Enjoy 🙂 !!!
In this primer, we will demonstrate how one can download, deploy, and use LLM models in the GGUF format on the Ollama platform.
Here is the link to the article on running GGUF models on Ollama:
Quick Primer on Running GGUF models on Ollama
Enjoy 🙂 !!!
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 🙂 !!!
Posted my next article on LinkedIn and here is the link:
Cautionary Reminder on Major Updates to Prod !!!
Hope is useful for others !!!