Watch Machine Learning Tutorial Python - 10 Support Vector Machine (SVM) Video Tutorial

𝐂𝐥𝐚𝐫𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧 (𝐓𝐢𝐦𝐞𝐬𝐭𝐚𝐦𝐩: 𝟓:𝟎𝟓): The graph labels should be: Graph 1 → High C (Weak Regularization) Graph 2 → Low C (Strong Regularization) Note: Although 𝐂 is called the regularization parameter, it is 𝐢𝐧𝐯𝐞𝐫𝐬𝐞𝐥𝐲 𝐩𝐫𝐨𝐩𝐨𝐫𝐭𝐢𝐨𝐧𝐚𝐥 𝐭𝐨 𝐭𝐡𝐞 𝐬𝐭𝐫𝐞𝐧𝐠𝐭𝐡 𝐨𝐟 𝐫𝐞𝐠𝐮𝐥𝐚𝐫𝐢𝐳𝐚𝐭𝐢𝐨𝐧. ------------- Support vector machine (SVM) is a popular classification algorithm. This tutorial covers some theory first and then goes over python coding to solve iris flower classification problem using svm and sklearn library. We also cover different parameters such as gamma, regularization and how to fine tune svm classifier using these parameters. Basically the way support vector machine works is it draws a hyper plane in n dimension space such that it maximizes the margin between classification groups. #MachineLearning #PythonMachineLearning #MachineLearningTutorial #Python #PythonTutorial #PythonTraining #MachineLearningCource #SupportVectorMachine #SVM #sklearntutorials #scikitlearntutorials Code: https://github.com/codebasics/py/blob/master/ML/10_svm/10_svm.ipynb Exercise: Open above notebook from github and go to the end. Exercise solution: https://github.com/codebasics/py/blob/master/ML/10_svm/Exercise/10_svm_exercise_digits.ipynb Topics that are covered in this Video: 0:00 Introduction 0:20 Theory (Explain support vector machine using sklearn iris dataset flower classification problem) 3:11 What is Gamma? 4:21 What is Regularization? 5:27 Kernel 6:32 Coding (Start) 18:08 sklearn.svm SVC 21:41 Exercise (Classify hand written digits dataset from sklearn using SVM) Do you want to learn technology from me? Check https://resources.codebasics.io/o9z6PE for my affordable video courses. Next Video: Machine Learning Tutorial Python - 11 Random Forest: https://www.youtube.com/watch?v=ok2s1vV9XW0&list=PLeo1K3hjS3uvCeTYTeyfe0-rN5r8zn9rw&index=12 Populor Playlist: Data Science Full Course: https://www.youtube.com/playlist?list=PLeo1K3hjS3us_ELKYSj_Fth2tIEkdKXvV Data Science Project: https://www.youtube.com/watch?v=rdfbcdP75KI&list=PLeo1K3hjS3uu7clOTtwsp94PcHbzqpAdg Machine learning tutorials: https://www.youtube.com/watch?v=gmvvaobm7eQ&list=PLeo1K3hjS3uvCeTYTeyfe0-rN5r8zn9rw Pandas: https://www.youtube.com/watch?v=CmorAWRsCAw&list=PLeo1K3hjS3uuASpe-1LjfG5f14Bnozjwy matplotlib: https://www.youtube.com/watch?v=qqwf4Vuj8oM&list=PLeo1K3hjS3uu4Lr8_kro2AqaO6CFYgKOl Python: https://www.youtube.com/watch?v=eykoKxsYtow&list=PLeo1K3hjS3uv5U-Lmlnucd7gqF-3ehIh0&index=1 Jupyter Notebook: https://www.youtube.com/watch?v=q_BzsPxwLOE&list=PLeo1K3hjS3uuZPwzACannnFSn9qHn8to8 Tools and Libraries: Scikit learn tutorials Sklearn tutorials Machine learning with scikit learn tutorials Machine learning with sklearn tutorials To download csv and code for all tutorials: go to https://github.com/codebasics/py, click on a green button to clone or download the entire repository and then go to relevant folder to get access to that specific file. 🌎 My Website For Video Courses: https://resources.codebasics.io/o9z6PE Need help building software or data analytics and AI solutions? My company https://www.atliq.com/ can help. Click on the Contact button on that website. #️⃣ Social Media #️⃣ 🔗 Discord: https://discord.gg/r42Kbuk 📸 Codebasics Instagram: https://www.instagram.com/codebasicshub/ 🔊 Codebasics Facebook: https://www.facebook.com/codebasicshub 📝 Codebasics LinkedIn: https://www.linkedin.com/company/codebasics/ 📱 Codebasics X handle: https://twitter.com/codebasicshub 📸 Dhaval's Instagram: https://www.instagram.com/dhavalsays/ 📝 Dhaval's LinkedIn: https://www.linkedin.com/in/dhavalsays/ 📱 Dhaval's X handle: https://x.com/dpcodebasics 🔗 Patreon: https://www.patreon.com/codebasics?fan_landing=true