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Rethinking DevOps: A New Era
As we advance into 2024, the landscape of DevOps is undergoing a transformative shift. Emerging technologies, evolving methodologies, and changing business needs are redefining what it means to implement DevOps practices effectively. This article explores DevOps's key trends and adaptations as we navigate this digital technology transition.
Emerging Trends in DevOps
AI and ML Integration
The integration of artificial intelligence (AI) and machine learning (ML) within DevOps processes is no longer a novelty but a…
LangChain, Python, and Heroku – DZone
Since the launch and wide adoption of ChatGPT near the end of 2022, we’ve seen a storm of news about tools, products, and innovations stemming from large language models (LLMs) and generative AI (GenAI). While many tech fads come and go within a few years, it’s clear that LLMs and GenAI are here to stay.
Do you ever wonder about all the tooling going on in the background behind many of these new tools and products? In addition, you might even ask yourself how these tools—leveraged by both developer and end users—are run…
Optimizing Pandas Code: The Impact of Operation Sequence
Learn how to rearrange your code to achieve significant speed improvements.Continue reading on Towards Data Science »
Learn how to rearrange your code to achieve significant speed improvements.Continue reading on Towards Data Science »
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Setting Up Automated Model Training Workflows with AWS S3
The Open-Source Approach for Workflow AutomationContinue reading on Towards Data Science »
The Open-Source Approach for Workflow AutomationContinue reading on Towards Data Science »
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Understanding Impact of Advanced Retrievers on RAG Behavior through Visualization
Is context from non-redundant nearest neighbors sufficient for LLM to generate accurate responses?Continue reading on Towards Data Science »
Is context from non-redundant nearest neighbors sufficient for LLM to generate accurate responses?Continue reading on Towards Data Science »
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Getting started with Vector Databases
Learn about what they are, how they work and what you need to get up and running with them!Continue reading on Towards Data Science »
Learn about what they are, how they work and what you need to get up and running with them!Continue reading on Towards Data Science »
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Crafting a Custom Sports Activity Service
Enter the realm of Artificial Intelligence (AI), where machine learning models and intelligent algorithms are revolutionizing how we interact with data, make decisions, and predict outcomes. The fusion of AI with Node.js opens a portal to a multitude of possibilities, transforming the landscape of web services across various domains, including sports and fitness.
Lifecycle
At the base of the application, we going to have some sports activity daily suggestions which will be generated based on AI. That means we do an…
Four Graph-based Feature Engineering Ideas to Improve your ML models
Explore innovative graph-based feature engineering techniques using networkx in Python and uncover hidden insights in tabular data.Continue reading on Towards Data Science »
Explore innovative graph-based feature engineering techniques using networkx in Python and uncover hidden insights in tabular data.Continue reading on Towards Data Science »
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DIGITOUR: Automatic Digital Tours for Real-Estate Properties
An Automated Pipeline for Creating 3D Experiences from Equirectangular Images1. IntroductionThe demand for online real-estate tools has increased drastically due to the ease of accessibility to the Internet, especially in countries like India. There are many online real-estate platforms for owners, developers, and real-estate brokers to post properties for buying and renting purposes. Daily, these platforms receive 8,000 to 9,000 new listings. Until now, the users on these platforms view images, snapshots, or videos,…
AI-Driven API and Microservice Architecture Design
Incorporating AI into API and microservice architecture design for the Cloud can bring numerous benefits. Here are some key aspects where AI can drive improvements in architecture design:
Intelligent planning: AI can assist in designing the architecture by analyzing requirements, performance metrics, and best practices to recommend optimal structures for APIs and microservices.
Automated scaling: AI can monitor usage patterns and automatically scale microservices to meet varying demands, ensuring efficient resource…