Janakiram MSV on AutoResearch's Automated ML Experiments

🐍📰 In this tutorial, you'll learn all about the k-Nearest Neighbors (kNN) algorithm in Python, including how to implement kNN from scratch, kNN hyperparameter tuning, and improving kNN performance using bagging #python

Your model is only as good as your labels. Inadequate annotation results in poor detection, regardless of algorithm quality. This guide details how to develop a dual-engine barcode annotation tool in Python to enhance accuracy. https://lnkd.in/gr8-88ky #Python #MachineLearning #Annotation #DevTools

🚀 Just published a new article on Generative AI in Python. I’ve covered how to build production-ready systems using concepts like FastAPI, RAG, and performance optimization. If you're into Python, backend development, or AI, this might be useful. #GenerativeAI #Python #SoftwareEngineering

Curious how to integrate your Python code into a C++ project? I took some time to flesh out my previous article on calling Python scripts from with C++ with input- and output-arguments. I added figures, added content, made the text more readable, and added a section on multithreading. No generative models used. You can find the updated article here, and more posts to follow soon: https://lnkd.in/dWFngEvV

Dug a bit into LLM inference engines, and turns out you don't really need C++/CUDA for the core kernels. Wrote a post at https://lnkd.in/gEGX6cGs about performant Python inference using Numba, CuTe-DSL, CuTile, and NCCL4Py.

In this article, you will learn how to use Python decorators to improve the reliability, observability, and efficiency of machine learning systems in production.

“InsightFace Explained: From Images to Embeddings in Python Using Deep Learning” Most tutorials focus on how to use a library. In this article, I focused on something more important: 👉 Understanding how InsightFace works under the hood 👉 How images are converted into embeddings 👉 How face matching actually works 👉 And how to build a simple, production-style pipeline using Django I’ve broken everything down step by step—from uploading a selfie to retrieving matching photos from a database. If you’re working with: Computer Vision Machine Learning Python backend systems Or building real-world AI applications this might be useful for you. Would love your feedback 👇 Here is the link to read my article https://lnkd.in/gARtC9Ng #ArtificialIntelligence #MachineLearning #ComputerVision #Python #DeepLearning

Every AI Agent can write a python script to reverse a linked list (I have no idea what that means). But how many AI Agents can order your Phở for tomorrow 👇

🚨 NEW POST ~ Learn to build GPT from scratch in plain Python without using any deep learning framework or libraries ➡️ https://lnkd.in/e88j9T6Y

Built a Tic Tac Toe AI from scratch using the Minimax algorithm in Python ♟️ link :- https://lnkd.in/dM7CZhHN What started as a simple game turned into a deep dive into how machines actually “think” and make decisions. I implemented the entire logic from scratch — using recursion and decision trees to simulate every possible move and choose the optimal one. The result? An AI that’s (almost) impossible to beat 😅 Key takeaways from this project: • Understood how Minimax evaluates game states and ensures the best outcome • Learned how recursion can model real decision-making processes • Realized how powerful simple algorithms can be when applied correctly This project wasn’t just about building a game—it was about understanding the logic behind intelligent systems. have a great day guys, stay safe and healthy, grind hard and just do your best everyday. bye 😊 #Python #Algorithms #ArtificialIntelligence #Minimax #GameAI #TicTacToe #SoftwareDevelopment #Coding #BuildInPublic #LearningJourney #ProblemSolving #TechProjects