AI Agents Simplified: Thermostat Architecture

This metaphor changed how I explain AI agents to non-technical people. Once you say "thermostat," the mystique evaporates — and what's left is just engineering. That's why I wrote the book.

A hands-on collection of real-world implementations to build LLM-powered applications using Python, LangChain, and Hugging Face. What’s inside: • RAG pipelines (Chroma / FAISS) • Custom/opensource LLM integrations • Memory & prompt engineering • Autonomous agents (ReAct style) Built with 2026 best practices to help you get started with production-ready #AI apps. #LLM #LangChain #HuggingFace #Python #MachineLearning #RAG #GenerativeAI https://lnkd.in/gqQ5sZVc

Machine Learning Image Data using mahotas #machinelearning #datascience #imagedata #mahotas Mahotas is a computer vision and image processing library for Python. It includes many algorithms implemented in C++ for speed while operating in numpy arrays and with a very clean Python interface. Mahotas currently has over 100 functions for image processing and computer vision and it keeps growing. Some examples of mahotas functionality : watershed convex points calculations. hit & miss. thinning Zernike & Haralick, local binary patterns, and TAS features. morphological processing Speeded-Up Robust Features (SURF), a form of local features thresholding convolution. Sobel edge detection. The release schedule is roughly one release every few months and each release brings new functionality and improved performance. The interface is very stable, though, and code written using a version of mahotas from years back will work just fine in the current version, except it will be faster (some interfaces are deprecated and will be removed after a few years, but in the meanwhile, you only get a warning). https://lnkd.in/gEWAMFRB

🐍📰 How to Use the OpenRouter API to Access Multiple AI Models via Python Access models from popular AI providers in Python through OpenRouter's unified API with smart routing, fallbacks, and cost controls https://lnkd.in/gbfvdfSk

🚀 Post 2 — Day 24 🧠 Day 24 – The 30-Day AI & Analytics Sprint Today’s discussion question is about Python Performance ⚡ When working with loops in Python, the way we write our code can significantly affect: Program performance Memory usage Time complexity 💬 Discussion Question How does the way we use loops in Python affect program performance? Discuss the following points: 🔹 What is the difference between a traditional loop and List Comprehension? 🔹 How do Nested Loops impact Time Complexity? 🔹 When is it better to replace loops with built-in functions like: map() filter() sum() 🔹 What techniques can improve performance when working with large datasets? 💡 Python is powerful, but writing Pythonic and optimized code makes a huge difference. Curious to read your thoughts 👇 #Python #AI #MachineLearning #Programming #PerformanceOptimization #DataAnalytics

One reason Python became so popular: Readability. Compare this idea with many other languages: if user.is_authenticated: process_request() The syntax is intentionally simple. Python was designed to be almost like writing pseudocode. That design philosophy explains why Python dominates areas like: • Data Science • AI • Automation • Backend scripting Sometimes the best optimization is not speed. Sometimes it's developer productivity.

Your Python team might be optimizing the wrong things. 🐍 Tooling, runtimes, and deployment practices are evolving fast. Teams are struggling to keep up. ⚡ What are the most important shifts? 🎙️ Talk Python Training podcast host Michael Kennedy, Calvin Hendryx-Parker and Peter Wang discuss: https://lnkd.in/eTKXNebf

💭 I still remember my first Python program… It was just one line: print("Hello, World!") Nothing fancy. No big achievement. But somehow… it felt powerful. Like I had just unlocked a new language—one that computers understand. At first, Python looked too simple. No complex syntax, no overwhelming rules… just clean, readable code. But that simplicity? That’s where the real magic was hiding. Slowly, “Hello World” turned into small scripts… Scripts turned into projects… And projects turned into confidence. 🐍 Python isn’t just a programming language. It’s a starting point. A gateway into AI, Data Science, Automation, Web Development, and so much more. And the best part? You don’t need to be a genius to start. Just curious enough to try. ✨ Every expert was once a beginner staring at a blinking cursor. So if you’ve been thinking about starting… This is your sign. #Python #CodingJourney #LearnToCode #Programming #TechStory #DeveloperLife #AI #DataScience #CareerGrowth🚀

Machine Learning Time Series Data using adtk #machinelearning #datascience #timeseriesdata #adtk Anomaly Detection Toolkit (ADTK) is a Python package for unsupervised / rule-based time series anomaly detection. As the nature of anomaly varies over different cases, a model may not work universally for all anomaly detection problems. Choosing and combining detection algorithms (detectors), feature engineering methods (transformers), and ensemble methods (aggregators) properly is the key to build an effective anomaly detection model. This package offers a set of common detectors, transformers and aggregators with unified APIs, as well as pipe classes that connect them together into a model. It also provides some functions to process and visualize time series and anomaly events. https://lnkd.in/gx3Sq3MD

🚀 Built a Random Story Generator using Python Excited to share my latest mini-project where I combined creativity with coding! 🔹 The program generates random stories based on different genres like Horror 👻, Sci-Fi 🚀, and Comedy 😂 🔹 It uses Python concepts like lists, random module, loops, and file handling 🔹 Each story includes a unique twist ending to make it more interesting 🔹 Stories are automatically saved into a file for future use 💡 This project helped me strengthen my logic building and understand how to structure real-world programs Sample Output: "One day a robot in the future city discovered a portal. Suddenly, it hacked someone. But it was a trap!" I’m currently working on improving this project by adding: ➡️ GUI interface (Tkinter) ➡️ More advanced story logic ➡️ User customization GitHub Repo Link :- https://lnkd.in/gmPkM3gk Would love your feedback and suggestions! 🙌 #Python #Coding #Projects #BeginnerProjects #Learning #AI #DeveloperJourney Python #Automation #BeginnerProject #CodingJourney #LearningByDoing