Artificial Intelligence

🔗 Most ML roadmaps

If you’re tired of bloated diagrams and endless theory, this one’s for you.

This is the 10-step roadmap I wish someone gave me earlier focused on real-world impact, not just flashy model builds. Swipe through to see: ✅ The core skills you actually need ✅ What separates you from junior talent ✅ What most self-taught engineers skip Whether you’re transitioning from data analyst, coming from software dev, or just trying to stop tutorial-hopping...

🤖 10 UNKNOWN AI TOOLS....

📌 Awesome CursorRules: A repository of Cursor AI recipes. Awesome CursorRules is a collection of .cursorrules recipe files for fine-tuning the behavior of Cursor AI. The author of the repository has collected dozens of templates that adapt code generation to specific projects: from mobile applications to blockchain solutions. The main feature of .cursorrules is flexibility. Developers can write rules that will make AI hints more relevant: for example, take into account the team's code style or the architectural features of the project. This not only speeds up the work, but also reduces the risk of errors. The collection includes almost all areas of development: frontend (Angular, NextJS, Qwik, React, Solid, Svelte, Vue), backend (Deno, Elixir, ES, Go, Java, Lavarel, NodeJS, Python, TypeScript, WordPress), mobile development (React Native, SwiftUI, TypeScript, Android, Flutter) and specific tasks - integration with Kubernetes or optimization for SOLID principles. For beginners, there are step-by-step instructions: just copy the file into the project or install the extension for VS Code. Judging by the reviews, Awesome CursorRules has already become a must-have for those who want to get the most out of Cursor AI. 🖥 GitHub

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Meme of the day: Waymo robotaxi is circling around one point due to a malfunction. The company has already responded and promised to fix Delamain's crazy chariot. #meme

📂 Full description Explore the world of machine learning on edge devices with this hands-on course. Robert Gallup—a technologist, designer, and maker—guides you through basic machine learning concepts and workflow. Set up the necessary tools and hardware to develop a voice-driven prototype using the Arduino Nano 33 BLE Sense microcontroller. Discover how to use the Edge Impulse platform to acquire data, train a machine learning model, and generate code for your prototype. Upload and modify the code to complete your prototype using the Arduino IDE. Finally, explore practical challenges in deploying ethical machine learning on edge devices. By the end of this course, you'll be equipped to create your own intelligent prototypes, enhancing your technical portfolio and practical problem-solving abilities.

🔅 Machine Learning Foundations: Prototyping with Edge Impulse 🌐 Author: Robert Gallup 🔰 Level: Beginner ⏰ Duration: 1h 9m

🌀 Discover how to collect data, train models, and deploy code on the Arduino Nano 33 BLE Sense, making intelligent and responsive prototypes.

📗 Topics: Arduino IDE, Machine Learning 📤 Join Artificial Intelligence and Machine Learning for more courses

📖 5 Steps For Data Pre-processing

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📂 Full description Explore the ins and outs of hacking machine learning with the cybersecurity training experts at Infosec Institute. Deep dive into topics such as hacking a CAPTCHA system, fuzzing a target, evading malware detection, and attacking machine learning systems. Plus, learn about deepfakes and how to perform backdoor attacks on machine learning. This course was created by Infosec Institute. We are pleased to host this training in our library.