Artificial Intelligence

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

🔅 PREMIUM CHANNELS -◦-◦--◦--◦-◦--◦--◦-◦--◦--◦-◦--◦- 🔰 The Coding Space -◦-◦--◦--◦-◦--◦--◦-◦-- 218k| 🔰 Linkedin Learning Courses 130k| 🔰 Premium Udemy Courses 128k| 🔰 Web Development -◦-◦--◦- 109k| 🔰 Learn Python 096k| 🔰 JavaScript Courses 079k| 🔰 Machine Learning -◦-◦--◦- 064k| 🔰 DevOps Tutorials 061k| 🔰 Learn React and NextJs 060k| 🔰 Data Analysis and Databases -◦-◦--◦- 052k| 🔰 Linux and DevOps 045k| 🔰 100 Days of Python 044k| 🔰 Best Telegram Channels -◦-◦--◦- 042k| 🔰 Business Training 042k| 🔰 ChatGPT Mastery 037k| 🔰 Mobile Development -◦-◦--◦- 036k| 🔰 Zero to Mastery 035k| 🔰 Udemy Learning 033k| 🔰 Codedamn Courses -◦-◦--◦- 032k| 🔰 Linkedin Learning 032k| 🔰 React 101 030k| 🔰 Crypto Lessons -◦-◦--◦- 027k| 🔰 Coding Interview 023k| 🔰 Telegram's Shorts -◦-◦--◦--◦-◦--◦--◦-◦-- 🔰 Add Your Channel -◦-◦--◦--◦-◦--◦--◦-◦--◦--◦-◦--◦- 🔰 2hrs on top & 8hrs in channel!

📂 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.

🔅 Machine Learning for Red Team Hackers by Infosec 🌐 Author: Infosec Institute 🔰 Level: Intermediate ⏰ Duration: 3h 39m

🌀 Learn the various techniques used in hacking machine learning.

📗 Topics: Ethical Hacking, Machine Learning, Red Teaming 📤 Join Artificial Intelligence and Machine Learning for more courses

🤗 HuggingFace is offering 9 AI courses for FREE! These 9 courses covers LLMs, Agents, Deep RL, Audio and more 1️⃣ LLM Course: https://huggingface.co/learn/llm-course/chapter1/1 2️⃣ Agents Course: https://huggingface.co/learn/agents-course/unit0/introduction 3️⃣ Deep Reinforcement Learning Course: https://huggingface.co/learn/deep-rl-course/unit0/introduction 4️⃣ Open-Source AI Cookbook: https://huggingface.co/learn/cookbook/index 5️⃣ Machine Learning for Games Course https://huggingface.co/learn/ml-games-course/unit0/introduction 6️⃣ Hugging Face Audio course: https://huggingface.co/learn/audio-course/chapter0/introduction 7️⃣ Vision Course: https://huggingface.co/learn/computer-vision-course/unit0/welcome/welcome 8️⃣ Machine Learning for 3D Course: https://huggingface.co/learn/ml-for-3d-course/unit0/introduction 9️⃣ Hugging Face Diffusion Models Course: https://huggingface.co/learn/diffusion-course/unit0/1

🔅 PREMIUM CHANNELS -◦-◦--◦--◦-◦--◦--◦-◦--◦--◦-◦--◦- 🔰 The Coding Space -◦-◦--◦--◦-◦--◦--◦-◦-- 217k| 🔰 Linkedin Learning Courses 129k| 🔰 Premium Udemy Courses 128k| 🔰 Web Development -◦-◦--◦- 108k| 🔰 Learn Python 096k| 🔰 JavaScript Courses 078k| 🔰 Machine Learning -◦-◦--◦- 064k| 🔰 DevOps Tutorials 060k| 🔰 Learn React and NextJs 059k| 🔰 Data Analysis and Databases -◦-◦--◦- 052k| 🔰 Linux and DevOps 045k| 🔰 100 Days of Python 043k| 🔰 Best Telegram Channels -◦-◦--◦- 041k| 🔰 Business Training 041k| 🔰 ChatGPT Mastery 036k| 🔰 Mobile Development -◦-◦--◦- 036k| 🔰 Zero to Mastery 035k| 🔰 Udemy Learning 033k| 🔰 Codedamn Courses -◦-◦--◦- 032k| 🔰 Linkedin Learning 031k| 🔰 React 101 030k| 🔰 Crypto Lessons -◦-◦--◦- 027k| 🔰 Coding Interview 023k| 🔰 Telegram's Shorts -◦-◦--◦--◦-◦--◦--◦-◦-- 🔰 Add Your Channel -◦-◦--◦--◦-◦--◦--◦-◦--◦--◦-◦--◦- 🔰 2hrs on top & 8hrs in channel!

🔥 Google has introduced InstructPipe , an AI editor for ML pipelines that works via text queries. ❔ What is InstructPipe? InstructPipe is an AI assistant that transforms text commands into visual flowcharts representing machine learning pipelines. The system uses two large language model (LLM) modules and a code interpreter to generate pseudocode and visualize it in a graph editor. This is a low-code approach: you simply connect ready-made components (nodes) without writing code. 🌟 How does this work? 1️⃣ The user enters a text instruction describing the desired pipeline. 2️⃣ LLM modules process the instruction and generate the corresponding pseudocode. 3️⃣ The code interpreter converts pseudocode into a visual flowchart that you can edit and customize. ✔️ Benefits of InstructPipe 🟡 Accessibility: Allows newcomers to programming to create complex ML pipelines without having to write code. 🟡 Flexibility: Accepts text description in any form, no strict format. 🟡 Lower barrier to entry: Simplifies the process of learning and prototyping ml projects. 🔜 Read more

🔗 Top 5 machine learning projects: 1. Predicting House Prices: Build a machine learning model that predicts house prices based on features such as location, size, number of bedrooms, etc. This project will help you understand regression techniques and feature engineering. 2. Image Classification: Create a model that can classify images into different categories such as cats vs. dogs, fruits, or handwritten digits. This project will introduce you to convolutional neural networks (CNNs) and image processing. 3. Sentiment Analysis: Develop a sentiment analysis model that can classify text data as positive, negative, or neutral. This project will help you learn natural language processing techniques and text classification algorithms. 4. Credit Card Fraud Detection: Build a model that can detect fraudulent credit card transactions based on transaction data. This project will help you understand anomaly detection techniques and imbalanced classification problems. 5. Recommendation System: Create a recommendation system that suggests products or movies to users based on their preferences and behavior. This project will introduce you to collaborative filtering and recommendation algorithms.