#Koina Machine Learning Model Github

POV: you combined Gemini 3.1 + Opus 4.6 and built your own CIA style command console. A dev just shared this and it’s going viral on X right now. This isn’t just experimenting with AI tools. It’s a full geospatial system running in the browser. What happens when you wire the models together: → Spatial reasoning + system logic Maps, coordinates, and live data processed in real time → Live aircraft tracking → Satellite and traffic overlays → Full scene detection → Intelligence style UI Not one magic model.But specialised systems working together. Comment “AI” and I’ll send you the exact setup behind this. Credit to bilawalsidhu on X for making this. #ai #coding #tech #gemini #claude

Machine Learning 🤍

Probably the last day as well #machinelearning #chatgpt #python #coding #softwareengineer

Making building your own ML model a little less intimidating if it’s your first time :) #ai #machinelearning

Comment “ML” and I’ll send you the links👇 Machine learning doesn’t have to feel overwhelming. With the right guidance, complex topics like models, training, and prediction start making real sense 🧠 📌 Check out these beginner-friendly ML videos: 1️⃣ Learn Machine Learning Like a Genius – by InfiniteCodes 2️⃣ All ML Concepts Explained in 22 Minutes – by InfiniteCodes 3️⃣ ML for Everybody (Full Course) – by FreeCodeCamp If terms like neural networks, supervised learning, or algorithms have ever confused you, these tutorials simplify everything into clear, practical explanations you can actually follow. Instead of getting stuck in heavy math or abstract theory, you’ll build strong intuition around how machine learning works — from foundational concepts to real-world AI applications. Whether you're interested in artificial intelligence, data science, Python projects, or future-proof tech skills, this is a powerful place to begin. ⭐ Save this so you don’t lose it, share it with someone learning AI, and start making machine learning finally click.

If you want to learn AI or Machine Learning, then you need to check out these 4 Github Repositories. They are beginner friendly and easy to follow along. Comment AI to get the Links in your DM

Here’s your full roadmap on how to get into machine learning. Comment “Roadmap” to get the pdf. Save and follow for more. #ai #machinelearning #coding #programming #cs

If you were starting Machine Learning in 2026, what would your roadmap look like? ㅤ #MachineLearning #MLJourney #LearnML #AI2026 #DataScienceJourney

Machine Learning doesn’t click until you build daily. This repo forces that habit in 100 days. Like and comment 'link' [100 days of ml, machine learning roadmap, ml projects, github ml, ai learning, data science basics, python ml, cs students, ai resources, learning by building]

Learn to Learn Machine Learning 👾 This one is basic af, and I’ve abstracted a lot of the complexity but we’ll get more complex as we go. (It was 54 seconds, then I yapped in the intro too much) If there are any topics you want me to cover, let me know #machinelearning #ai

ChatGPT, Gemini, or Qwen? Who Solved It? Who is the ultimate AI coder? 💻🤖 ​We are looking at a fascinating visual benchmark where different AI models—ChatGPT, Gemini, Qwen, and GLM 4.5—were tasked with generating code to create a bouncing ball animation within a specific geometric shape. ​Why this is a valuable test: While generating text is easy for AI, creating functional code that respects geometric constraints and physics is a true test of its logical reasoning. ​Complexity: Each shape (from the square to the multi-sided polygon) requires the AI to calculate correct reflection angles and 'hitboxes'. ​The Winner: In many of these specific 'coding arena' tests, Qwen Coder has been outperforming others in terms of mathematical precision and clean execution. ​Pro Tip for Users: If you are using AI for coding, don't just look at the text it provides. Test its ability to handle Logic and Math. It’s the best way to know which model is right for your technical projects! ​Which model do you rely on for your daily tasks? 👇#AIProgramming #ChatGPT #GeminiAI #QwenCoder #CodingLife #ArtificialIntelligence #TechComparison #SoftwareDevelopment #PythonProgramming #LogicTest #FutureOfTech #AIModels #ComputerScience

Find all these topics at my GenAI Roadmap GitHub Repo —> genieincodebottle/generative-ai pdf location - https://github.com/genieincodebottle/generative-ai/blob/main/docs/genai_tech_stacks.pdf Prompt Engineering: Perfecting questions to get smarter AI answers. RAG (Retrieval-Augmented Generation): Blending real-time info with AI for accurate results. Agents: Specialized mini-AIs that complete tasks or answer on specific topics. LLMs (Large Language Models): Core of GenAI based on Transformer architecture that understand and generate text. Multimodal AI: AI that handles text, images, and more together for richer outputs. Fine-Tuning: Adjusting LLMs for specific jobs, like customer support or medical advice. LLM Evaluation: Measuring if AI responses are accurate and reliable. LLMOps: Managing and improving GenAI in production, think maintenance for models. AWS, Azure, Vertex AI: Leading cloud platforms powering AI capabilities. Transformers: The core architecture behind modern LLMs, making complex tasks easier. . . . . #generativeai #genai #technology #softwaredeveloper #softwareengineer #python #dataanalyst #datascientist #fullstackdeveloper #fullstackdevelopment #machinelearning #softwaredevelopment #artificialintelligence