support vector machines #maths #dataanlysis #datascience #machinelearning #statistics

📚 *RECOMMENDED BOOKS TO START WITH MACHINE LEARNING* ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ If you're new to ML, here are the 3 best books I recommend (I've personally read all of these): 1. Hands-On Machine Learning – the go-to practical ML guide: https://amzn.to/3UcGqSS 2. Mathematics for Machine Learning – deep dive into the theoretical aspects of ML: https://amzn.to/3IZgHe7 3. Designing Machine Learning Systems - practical strategies for building scalable ML solutions: https://amzn.to/4ojEqFX These are affiliate links, so buying through them helps support the channel at no extra cost to you — thanks 🙏 *Summary* ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ Support vectors are the key elements behind Support Vector Machines (SVM), one of the most powerful supervised learning algorithms in machine learning. This video explains what support vectors are, how they define the optimal separating hyperplane, why the margin matters, and how SVM works for classification problems. If you want to understand the geometry of SVM, maximum margin classifiers, and the intuition behind kernel methods, this explanation makes the concept clear and practical. *Follow Me* ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ 🐦 Twitter: @datamlistic https://twitter.com/datamlistic 📸 Instagram: @datamlistic https://www.instagram.com/datamlistic 📱 TikTok: @datamlistic https://www.tiktok.com/@datamlistic 👔 Linkedin: https://www.linkedin.com/company/datamlistic *Channel Support* ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ The best way to support the channel is to share the content. ;) If you'd like to also support the channel financially, donating the price of a coffee is always warmly welcomed! (completely optional and voluntary) ► Patreon: https://www.patreon.com/datamlistic ► Bitcoin (BTC): 3C6Pkzyb5CjAUYrJxmpCaaNPVRgRVxxyTq ► Ethereum (ETH): 0x9Ac4eB94386C3e02b96599C05B7a8C71773c9281 ► Cardano (ADA): addr1v95rfxlslfzkvd8sr3exkh7st4qmgj4ywf5zcaxgqgdyunsj5juw5 ► Tether (USDT): 0xeC261d9b2EE4B6997a6a424067af165BAA4afE1a