Explores the inner workings of microservices architecture, shedding light on its guiding principles, deployment strategies, monitoring tools, challenges, and best practices.
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Find out why software product engineering projects fail. And learn how top companies avoid these failures.
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In this detailed guide, Simform walks you through every ownership cost—from development and infrastructure to maintenance, support, and retirement. Learn why TCO goes beyond initial expenses, how it empowers CTOs to align tech investments with long‑term business value, and get a clear, actionable framework for assessing and optimizing your product’s lifecycle costs. The guide also explores cloud services, automate testing, and ensure continuous monitoring to reduce long-term operational costs.
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A practical guide with proven tips and best practices to help your engineering team grow sustainably.
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Learn everything about hallucinations in LLMs. Discover their types and causes along with strategies for how to detect and reduce them in your models.
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Google Bard vs ChatGPT: Unveiling Strengths, Weaknesses, and Real-World Applications!
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All you need to know about the use cases, benefits, and shortcomings of Meta AI’s latest open-source large language model.
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Everything you need to know about Artificial intelligence in IoT: Benefits, use cases, challenges, and how to get started with it.
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Everything you need to know about diffusion models with examples: Benefits, use cases, challenges, and how to get started.
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Cost-effective management is essential for multi-tenant SaaS environments on AWS. Explore the journey towards SaaS profitability, the associated costs, and the role of multi-tenant environments with actual examples.
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Explore the top 15 open-source LLMs in 2024 that are redefining language technology. Find out how they work and compare their features with our insightful guide.
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Assuming your familiarity with machine learning – where algorithms and data enable computers to learn and decide, let’s look at the two models that emerge while applying these algorithms to real-world issues: supervised and unsupervised learning.
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