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Here's what i found out while i googled Master Python: It's the go-to language for AI, so get comfortable with its basics first. Learn ML Fundamentals: Understand concepts like data types, algorithms (linear regression, decision trees), and how to evaluate models. Dive into Libraries: Start using popular tools like scikit-learn for traditional ML, then explore TensorFlow or PyTorch for deep learning. Hands-On Projects: Build small models, starting simple, using datasets from Kaggle or similar platforms. Utilize Online Resources: Take free courses (Coursera, edX, fast.ai) and join communities for guidance and collaboration.
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Excited to dive into Hands-on Machine Learning with Scikit-Learn, Keras & TensorFlow Machine learning is evolving rapidly, and this book is a goldmine for anyone looking to build intelligent systems using the latest tools and frameworks. From Scikit
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Hi everyone , if you are a beginner in Data Science or wish to start , then this post is for you. Linear Regression is one of the first things you need to learn in ML. It is not just about the code . Code is not the important thing, you can make Chat
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🌦 Weather Prediction Using Machine Learning 📊 I’m excited to share one of my recent projects — a Weather Prediction Model built using machine learning! 🚀 📌 Project Overview: The model was trained to predict temperature based on historical weath
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✅ Actively Looking for Full-Time Opportunities 📍 Location: Bangalore / Remote / Hybrid 💼 Roles Targeted: Data Analyst / Data Engineer AI/ML Engineer (GenAI, NLP, DL) Software Developer (Python, Backend, APIs) Cloud Engineer / DevOps (Entry-leve
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My Favorite AI & ML Books That Shaped My Learning Over the years, I’ve read tons of books in AI, ML, and LLMs — but these are the ones that stuck with me the most. Each book on this list taught me something new about building, scaling, and underst
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