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Tag: image

  • Agentic AI using Autonomous Platforms (n8n, make, zapier)

    Agentic AI using Autonomous Platforms (e.g., n8n) (2025) In 2025, the convergence of Agentic AI and Autonomous Platforms like n8n is revolutionizing automation. Agentic AI refers to AI systems capable of perceiving their environment, making decisions, and taking actions to achieve specific goals without constant human intervention. When integrated with autonomous platforms, these agents can… Read more

  • Integrating AI in Automation Workflows

    Integrating AI in Automation Workflows (2025) In 2025, integrating Artificial Intelligence (AI) into automation workflows is no longer a futuristic concept but a practical way to enhance efficiency, make more intelligent decisions, and handle complex tasks that traditional rule-based automation struggles with. AI can add layers of understanding, prediction, and adaptation to your automated processes.… Read more

  • Details of Vector Embeddings

    Details of Vector Embeddings Vector embeddings are numerical representations of data points (such as words, sentences, images, or even abstract concepts) in a multi-dimensional space. The core idea is to translate complex information into a list of numbers (a vector) that captures the underlying meaning, features, and relationships of the data. Multi-dimensional Space: Embeddings exist… Read more

  • Comparative Analysis: Building AI Applications in AWS, GCP, and Azure

    Building Artificial Intelligence (AI) applications requires robust infrastructure, powerful compute resources, comprehensive toolkits, and scalable services. Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft Azure are the leading cloud providers, each offering a rich set of AI and Machine Learning (ML) services. This analysis compares their key offerings and approaches for building AI… Read more

  • Top 25 Must-Have AI Tools

    Artificial intelligence is rapidly transforming various industries, and having the right AI tools at your disposal can significantly enhance productivity, creativity, and decision-making. This list highlights 25 must-have AI tools across different categories that are making waves. 1. ChatGPT (OpenAI) Category: Large Language Model Description: A powerful conversational AI capable of generating human-like text, answering… Read more

  • Top 30 AWS Cloud Interview Questions

    Preparing for an AWS Cloud interview? This comprehensive list of 30 key questions covers a wide range of AWS services and concepts, designed to help you demonstrate your understanding and expertise. 1. What is AWS? Answer: AWS (Amazon Web Services) is a comprehensive and broadly adopted cloud platform, offering over 200 fully featured services from… Read more

  • Autonomous Content Creation for Social Media Marketing using Agentic AI

    Here we implement agentic AI use case focusing on a creative and dynamic domain: Autonomous Content Creation for Social Media Marketing. Use Case: A marketing agency wants to automate the process of creating engaging content for various social media platforms for their clients. Instead of relying solely on human content creators, an agentic AI can… Read more

  • Distinguish the use cases for the primary vector database options on AWS

    Here we try to distinguish the use cases for the primary vector database options on AWS: 1. Amazon OpenSearch Service (with Vector Engine): 2. Amazon Bedrock Knowledge Bases (with underlying vector store choices): 3. Amazon Aurora PostgreSQL/RDS for PostgreSQL (with pgvector): 4. Amazon Neptune Analytics (with Vector Search): 5. Vector Search for Amazon MemoryDB for… Read more

  • Spring AI and Langchain Comparison

    A Comparative Look for AI Application DevelopmentThe landscape of building applications powered by Large Language Models (LLMs) is rapidly evolving. Two prominent frameworks that have emerged to simplify this process are Spring AI and Langchain. While both aim to make LLM integration more accessible to developers, they approach the problem from different ecosystems and with… Read more

  • Building a Hilariously Insightful Image Recognition Chatbot with Spring AI

    Building a Hilariously Insightful Image Recognition Chatbot with Spring AI (and a Touch of Sass)While Spring AI’s current spotlight shines on language models, the underlying principles of integration and modularity allow us to construct fascinating applications that extend beyond text. In this article, we’ll embark on a whimsical journey to build an image recognition chatbot… Read more

  • What is a Tensor

    In the realm of computer science, especially within the fields of machine learning and deep learning, a tensor is a fundamental data structure. Think of it as a generalization of vectors and matrices to potentially higher dimensions. Here’s a breakdown of how to understand tensors: Key Properties of Tensors: Why are Tensors Important in Machine… Read more

  • Vertex AI

    Vertex AI is Google Cloud‘s unified platform for machine learning (ML) and artificial intelligence (AI). It’s designed to help data scientists and ML engineers build, deploy, and scale ML models faster and more effectively. Vertex AI integrates various Google Cloud ML services into a single, seamless development environment. Key Features of Google Vertex AI: Google… Read more

  • Describing Prediction Input and Output

    In the context of machine learning, particularly when discussing model deployment and serving, prediction input refers to the data you provide to a trained model to get a prediction, and prediction output is the result the model returns based on that input. Let’s break down these concepts in more detail: Prediction Input: Prediction Output: Relationship… Read more

  • Training image classification and object detection models using Vertex AI

    You can train image classification and object detection models using Vertex AI. Here’s a comprehensive overview of the process: 1. Data Preparation 2. Training Options Vertex AI offers two main approaches for image model training: 3. Training Steps Here’s a general outline of the steps involved in training an image model on Vertex AI: 4.… Read more

  • Deploying a PyTorch model on Vertex AI

    Deploying a PyTorch model on Vertex AI involves several steps. Here’s a breakdown: 1. Prerequisites: 2. Steps Here’s a conceptual outline with code snippets using the Vertex AI Python SDK: 2.1 Upload Model Artifacts First, upload your trained model (house_price_model.pth) and preprocessor to your GCS bucket. 2.2 Create a Serving Container Since you’re using PyTorch,… Read more