Automate Execution Order with FRAMEWORM

Most frameworks make you modify core code to add a feature. 🔌 FRAMEWORM doesn't. Drop a file in /plugins. That's it. It's live. Auto-discovered. Validated. Registered. Available. No restarts. No config. No core changes. Ever. Build on top. Never inside. 📦 pip install frameworm 🔗 https://lnkd.in/d_h_7YCK #MachineLearning #MLOps #GenerativeAI #Python

My friend Aakash Ali built something that every ML engineer needs to see. 👇 FRAMEWORM — a Python framework where you NEVER touch core code again. Just drop a file in /plugins. It gets auto-discovered → validated → registered → live. No restarts. No config. No core changes. Ever. As someone who's felt the pain of modifying core code just to add one small feature — this hits different. 🙌 Aakash Ali, you're building the right things. Keep going! 🔥 📦 pip install frameworm 🔗 https://lnkd.in/d_h_7YCK #MachineLearning #MLOps #GenerativeAI #Python #OpenSource #AIEngineering #DeveloperTools #PluginArchitecture #BuildInPublic #ProudFriend

🚀 Generators: Memory-Efficient Iteration (Python) Generators are a special type of function that allows you to create iterators in a memory-efficient way. Instead of returning a list of values, generators yield values one at a time using the `yield` keyword. This is particularly useful when dealing with large datasets, as it avoids loading the entire dataset into memory. Generators can be implemented using either generator functions (using `yield`) or generator expressions (similar to list comprehensions but with parentheses). Generators are essential for optimizing memory usage and improving performance in data processing applications. #Python #PythonDev #DataScience #WebDev #professional #career #development

🚀 Day 47/60 – FastAPI to Flask Converted a FastAPI application into Flask. 🔄 Explored differences between frameworks and how flexibility helps in development. 💡 Understanding multiple frameworks makes you more adaptable as a developer. #AbTalksOnAI #FastAPI #Flask #Python #AI

Python cleaning tip that saved my time: Don’t loop over rows for simple replacements → use vectorized ops. Slow: --------------- for i in df.index: if df.at[i, 'status'] == 'act': df.at[i, 'status'] = 'active' Fast: ---------------- df['status'] = df['status'].replace('act', 'active') Vectorized = 10–100× faster. #Python #DataEngineering #Pandas #PerformanceTips #MomInTech #WomenInTech #LearningEveryday

What if you could improve LLM responses without training bigger models? That’s the idea behind Inferscale 0.1.1. A lightweight Python package that applies inference-time scaling techniques to produce higher-quality outputs—perfect for developers working within tight compute budgets. It’s simple, effective, and ready to use. Explore the repo and README: https://lnkd.in/giq8KJ5g Let me know what you think! #ArtificialIntelligence #LLM #Python #OpenSourceProject #AIInnovation #DeepLearning

🐍 Day 89 — Features and Labels Day 89 of #python365ai 📌 Features (X) → input variables Labels (y) → output Example: X = [size, rooms] y = price 📌 Why this matters: Clear distinction is essential for building ML models. 📘 Practice task: Identify features and labels in a dataset. #python365ai #Features #MachineLearning #Python

This problem demonstrates how dictionary comprehensions can create key–value pairs dynamically. It highlights how values can be generated from existing data while building a dictionary in a compact and readable way. A very useful technique when transforming datasets. THE ANSWER IS: B #Python #DictionaryComprehension #PythonChallenge #DataStructures #BuildInPublic

𝗟𝗮𝗻𝗴𝗖𝗵𝗮𝗶𝗻 𝗶𝘀𝗻'𝘁 𝗟𝗮𝗻𝗴𝗖𝗵𝗮𝗶𝗻 𝗮𝗻𝘆𝗺𝗼𝗿𝗲.  𝗟𝗹𝗮𝗺𝗮𝗜𝗻𝗱𝗲𝘅 𝗶𝘀𝗻'𝘁 𝗷𝘂𝘀𝘁 𝗥𝗔𝗚 𝗮𝗻𝘆𝗺𝗼𝗿𝗲. 2026 changed everything. Most developers haven't caught up. I put together the updated decision framework — which tool to use, when, and how the smartest teams are combining them in production. Swipe through 👉 Which stack are you running? 👇 #LangGraph #LlamaIndex #RAG #AIAgents #LLMOps #Python

Day 47/60 – FastAPI to Flask Converted a FastAPI application into Flask. Explored differences between frameworks and how flexibility helps in development. Understanding multiple frameworks makes you more adaptable as a developer. #AbTalksOnAI #FastAPI #Flask #Python #AI ABTalksOnAI