Machine Learning

In this post, I will guide you through the process of deploying Large Language Models (LLMs) on your personal computer and setting up a simple chatbot within one hour. This tutorial requires no advanced expertise in AI/ML or Python programming, familiarity with basic concepts is sufficient. We will cover everything from configuring the virtual environment to launching the web based User Interface (UI), providing a comprehensive, step-by-step guide along the way....

In Part 1, we covered about what are vector emdeddings and how to generate vector embedding for different data types. In this post we will learn about how the vector embeddings are managed and searched using a vector database like Milvus for your application. You can find the documentation here Architecture Milvus is an opensource vector database build on top of popular vector search libraries including Faiss, HNSW, DiskANN, SCANN and more....

In this post, we will learn about what are vector emdeddings and how to generate vector embedding for different data types. In the Part 2 I will explain how the vector embeddings are managed and searched using a vector database like Milvus for your application. What are vector embeddings? Vector embeddings are a way to convert data (Text, Image, Audio, Video or any other form of data) into numbers that represent their meaning and relationship (refered as a quantity with both magnitude and direction in Physics)....

Published in Analytics Vidhya https://medium.com/analytics-vidhya/tensorflow-lite-tflite-with-golang-37a326c089ff Tensorflow Lite commonly known as TFLite is used to generate and infer machine learning models on mobile and IoT(Edge) devices. TFLite made the on-device(offline) inference easier for multiple device architectures, such as Android, iOS, Raspberry pi and even backend servers. With TFLite you can build a lightweight server based inference application using any programming language with lightweight models, rather than using heavy Tensorflow models. As developers, we can simply use existing optimized research models or convert existing Tensorflow models to TFLite....

For the past few years IoT has become the hot topic in the technology world. This led the evolution of Edge computing to gain momentum and introduced new technologies. In mid 2017 Google announced the Tensorflow lite, which is an advanced and lightweight version of it’s predecessor Tensorflow mobile(Google is planning to replace Tensorflow mobile with Tensorflow lite in future). What is Edge computing ??? Edge computing is a method of optimizing cloud computing systems “by taking the control of computing applications, data, and services away from some central nodes (the “core”) to the other logical extreme (the “edge”) of the Internet” which makes contact with the physical world....