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llmgenerative-ai-toolsrunnable-primitives5 Jul 2026

LangChain Series #5: Runnables Explained — Building Blocks of LCEL and AI Workflows

In the previous article, we explored Chains and learned how LangChain allows us to connect prompts, language models, and output parsers into complete AI workflows using the LangChain Expression Language (LCEL).However, one important question remains:What actually makes these work…

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langchaingenerative-ai-toolsai-agent3 Jul 2026

LangChain Series #4: Chains Explained — Building AI Workflows with LCEL

This is the fourth article in my LangChain learning series. In the previous article, we explored prompts and learned how to communicate effectively with language models. Now it’s time to connect those components into complete AI workflows. In this article, we’ll explore Chains in…

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writing-promptslangchainprompt-engineering12 Jun 2026

LangChain Series #3: Prompts Explained — Prompt Templates, Chat Prompts, Dynamic Prompting…

🚀 LangChain Series #3: Prompts Explained — Prompt Templates, Chat Prompts, Dynamic Prompting, Structured Outputs, and Output ParsersPrompts are the foundation of every LLM application.No matter how powerful a model is, the quality of its output depends heavily on the instruction…

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embedding-modelsemantic-searchlangchain9 Jun 2026

LangChain Series #2: Models Explained — LLMs, Chat Models, and Embeddings with Practical…

🚀 LangChain Series #2: Models Explained — LLMs, Chat Models, and Embeddings with Practical ExamplesIntroductionWhen people start learning LangChain, they often think a “model” simply means ChatGPT or Gemini.In reality, LangChain provides a unified interface for working with diff…

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docker-composedockercontainerization8 Jun 2026

Docker Explained: Images, Containers, Dockerfiles, Docker Hub, and Docker Compose

Why do we need Docker?Imagine you’re a chef who has created the perfect cake recipe. You want your friends to bake the same cake, but each friend has a different kitchen, equipment, and ingredients.As a result, the cake may not turn out exactly the way you intended.Software devel…

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transfer-learningneural-networkscomputer-vision6 Jun 2026

Transfer Learning: Why Train From Scratch When Someone Has Already Done the Hard Work?

Imagine you want to build an image classification model that can distinguish between cats and dogs, or perhaps mobile phones and tablets.The first thought that comes to mind is:“Why not train my own neural network?”Sounds simple, right?Not quite.The Problem with Training Your Own…

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generative-ailangchainprompt-engineering6 Jun 2026

LangChain Series #1: Understanding Models, Prompts, Chains, Memory, Indexes, and Agents

Large Language Models (LLMs) such as GPT, Gemini, and Claude have made it easier than ever to build intelligent applications. However, developing production-ready AI systems often requires much more than simply calling an API.This is where LangChain comes inIn this article, we’ll…

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