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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

The ultimate AI/ML roadmap for beginners 👇 𝗠𝗮𝘁𝗵𝘀 What to learn: • Linear Algebra • Calculus • Statistics Resources: • Practical Statistics for Data Science( https://amzn.to/446czl5 ) • Mathematics for Machine Learning( https://amzn.to/441s

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

Day 2/100 : free AI resources sharing topic of day : machine learning Books ✓Machine Learning For Absolute Beginners by Oliver Theobald https://mrce.in/ebooks/Machine%20Learning%20for%20Absolute%20Beginners.pdf ✓Hands-On Machine Learning with

Top 10 Free AI Playgrounds For You to Try Curious about the future of AI? AI playgrounds are interactive platforms where you can experiment with AI models to create text, code, art, and more. They provide hands-on experience with pre-trained models

Here are some AI tools which are useful for the startups: 1. TensorFlow and PyTorch: Open-source frameworks for building machine learning models. 2. IBM Watson: Offers AI tools and services like natural language understanding and computer vision.

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

im a self taught developer, I've done ML on kaggle and ai engineer cources online then build few testing models and projects ,have over 900 questions done on leetcode over the year and have a almost every day consistency on GitHub for a full year no

AI Resources for Beginners Books: 1. Deep Learning. Illustrated Edition. Ian Goodfellow, Yoshua Bengio, and Aaron Courville. 2. Mathematics for Machine Learning. Deisenroth, A. Aldo Faisal, and Cheng Soon Ong. 3. Reinforcement learning, An Introd

Thrilled to share a key milestone in the development of LEWIS (Linux Environment Working Intelligence System) – our AI-powered cybersecurity assistant! Today, I trained and saved our first threat detection model using a pipeline of TfidfVectorizer a