AI and Machine Learning

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🔗 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.

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🔗 Instill Core is a universal tool for working with unstructured data. This open-source project offers a comprehensive solution for ETL processing, data preparation for AI, and deployment of LLM models. The platform combines document, image, and video processing into a single workflow, which is especially valuable for RAG scenarios and building AI pipelines. Instill Core can be easily integrated into existing systems via the Python/TypeScript SDK or CLI. Local execution is possible via Docker, and ready-made recipes allow you to quickly deploy PDF parsing, web scraping, or image segmentation. 🔗 GitHub

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Machine Learning Roadmap 👆

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We share practical tips, code snippets, tools, and real-world projects to help you grow as a developer — whether you're just starting out or looking to level up.

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📂 Full description Many of the worlds most exciting and innovative new tech projects leverage the power of machine learning. But if you want to set yourself apart as a data scientist or machine learning engineer, you need to stay up to date with the current tools and best practices for creating effective, predictable models.In this course, instructor Helen Sun shows you how to get up and running with PyTorch, the open-source machine learning framework known for its simplicity, performance, and APIs. Explore the basic concepts of PyTorch, including tensors, operators, and conversion to and from NumPy, as well as how to utilize autograd, which tracks the history of every computation recorded by the framework. By the end of this course, youll also be equipped with a new set of skills to get the most out of Torchvision, Torchaudio, and Torchtext.

🔅 Hands-On PyTorch Machine Learning 🌐 Author: Helen Sun 🔰 Level: Intermediate ⏰ Duration: 56m

🌀 Discover the fundamentals of creating machine learning models with PyTorch, the open-source machine learning framework.

📗 Topics: PyTorch, Machine Learning 📤 Join Artificial intelligence for more courses

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🔗 5 Trending AI Jobs You Can’t Miss in 2025! 🤖 💻 Machine Learning Engineer 👉🏻 Average Salary: $114,000 👉🏻 What They Do: Design and implement ML algorithms while collaborating with data scientists and engineers. 📊 📊 Data Scientist 👉🏻 Average Salary: $120,000 👉🏻 What They Do: Analyze data, build predictive models, and drive data-backed decisions. 📈 🔬 AI Research Scientist 👉🏻 Average Salary: $126,000 👉🏻 What They Do: Explore the future of AI by testing algorithms and driving innovation. 🌟 🤝 AI Ethic 👉🏻 Average Salary: $135,000 👉🏻 What They Do: Promote ethical AI development, address biases, and ensure fairness. 🌐 📈 AI Product Manager 👉🏻 Average Salary: $140,000 👉🏻 What They Do: Manage AI products for success, focusing on innovation and ethical impact. 🛠

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🔗 ML Libraries

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🔗 AI Agents for Beginners - A Course

This course has 10 lessons covering the fundamentals of building AI Agents.

🔰Each lesson covers its own topic so start wherever you like! 🔰There is multi-language support for this course. 🔗 Links: https://github.com/microsoft/ai-agents-for-beginners