Image Similarity Detection with Tensorflow 2.0 I used the image classification model from TensorFlow Hub Kinshuk Dutta New York
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The foundation of a successful EBX5 project is a well-structured series of workshops and activities that align business and IT teams with the project goals. The first critical step in this process is the Project Kickoff, where the objectives, roles, and key deliverables are clearly defined. 1. Project Kickoff: Setting the Stage for Success The project kickoff is where both business and IT teams come together to define the project’s scope, set expectations, and ensure alignment on key goals. Here are the major components of the kickoff phase: Project Scope Reminder (Business and IT Goals): During the kickoff, it’s essential…
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What is EBX5? EBX5 is a powerful Master Data Management (MDM) platform that helps organizations manage, govern, and synchronize their critical data assets. Whether dealing with master data, reference data, or metadata, EBX5 offers a centralized approach for managing these data classes, ensuring consistency, accuracy, and compliance across all systems. In this blog series, we will dive deep into the project methodology for successfully implementing EBX5 in an organization, ensuring seamless onboarding and integration of data classes. Data Classes in EBX5 EBX5 is designed to manage multiple types of data, including: Master Data: Data central to business operations, such as…
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Introduction: From Brains to Bytes In our previous post on AI, Machine Learning, and Deep Learning, we explored how machines can be trained to learn from data. One of the key driving forces behind this capability is a computational structure inspired by the human brain—Neural Networks. But what exactly are neural networks, and why have they become so central to modern AI? Let’s break it down in simple terms. What Is a Neural Network? A Neural Network is a series of algorithms that attempt to recognize patterns in data, similar to how our brains process information. It’s called a “network”…
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Table of Contents Introduction to NoSQL A Brief History of NoSQL MongoDB Install MongoDB on Mac Sample Project: Real-Time Data Storage with MongoDB Project Structure CRUD Operations Testing and Validation Conclusion and Next Steps Introduction to NoSQL A Brief History of NoSQL The journey of NoSQL databases began over several decades, with origins in hierarchical and file-based databases before becoming what we know today as “NoSQL.” NoSQL was first coined in 1998 by Carlo Strozzi to name a file-based database he developed. Ironically, this NoSQL database was actually relational but didn’t use SQL as its interface. Later, in 2009, the…
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SCALA & SPARK for Managing & Analyzing BIG DATA In this blog, we’ll explore how to use Scala and Spark to manage and analyze Big Data effectively. When I first entered the Big Data world, Hadoop was the primary tool. As I discussed in my previous blogs: [What’s so BIG about Big Data (Published in 2013)] [Apache Hadoop 2.7.2 on macOS Sierra (Published in 2016)] Since then, Spark has emerged as a powerful tool, especially for applications where speed (or “Velocity”) is essential in processing data. We’ll focus on how Spark, combined with Scala, addresses the “Velocity” aspect of Big…
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The Power of Scala in Data-Intensive Applications: Concluding the Series Originally posted January 2019 by Kinshuk Dutta After exploring Scala’s core functionalities, from basics to advanced concepts, we’re concluding this series by demonstrating how to bring everything together into a robust, scalable project. Scala’s versatility has made it a popular choice across industries, from fintech to retail, where companies harness its functional programming and concurrency features to handle data-intensive applications. This blog includes: An overview of how companies use Scala for a competitive edge. Tips, tricks, and best practices. Recommended resources to dive even deeper into Scala. A final, comprehensive…
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Chapter 1: Introduction In our previous blog of this series we have established the fact that EBX can be deployed as a container. We deployed EBX on Docker to achieve our goal, in continuation to the same we will see how can we use OpenShift for the same purpose. What is OpenShift OpenShift is a family of containerization software products developed by Red Hat. Its flagship product is the OpenShift Container Platform — an on-premises platform as a service built around Docker containers orchestrated and managed by Kubernetes on a foundation of Red Hat Enterprise Linux. The family’s other products provide this platform through different environments: OKD serves as the community-driven upstream (akin to the way…
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🧠 What Are Neural Networks? At the heart of deep learning lies the neural network—a mathematical model inspired by the human brain’s structure. These networks are made up of layers of artificial neurons that pass information from one layer to the next. Each neuron receives input, performs a weighted computation, and passes it to the next layer through an activation function. Neural networks are particularly well-suited to learning non-linear relationships from data. They allow machines to detect intricate patterns in images, audio, or text—without explicitly being programmed for the task. A basic neural network includes an input layer, one or…
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Getting Started with Machine Learning (ML) Machine learning projects typically follow a series of steps: data collection, data preprocessing, model selection, training, and evaluation. Here’s a breakdown of essential concepts and project ideas to help you get started. 1. Data Collection and Preprocessing Data is the foundation of any ML project. Collecting relevant, high-quality data ensures models have the information needed to identify patterns. Preprocessing steps—such as cleaning, normalization, and handling missing values—prepare raw data for analysis. Project Example: Predicting House Prices Using the famous Boston housing dataset, you can start by cleaning data and then normalizing it to improve…