Machine Learning Tutorial for Beginners
In this beginner friendly machine learning crash course, we will go over the theory and coding for all the required machine learning fundamentals. At the end, we have end to end capstone project as well. Resources: https://codebasics.io/resources/machine-learning-crash-course ⭐️ Timestamps ⭐️ 0:00:00 Intro 0:03:47 What is ML 0:13:33 Prereq 0:16:18 Linear Regression Single Variable 0:36:37 Linear Regression Multiple Variables 0:42:44 Train Test Split 0:54:12 Classification vs Regression 0:59:12 Logistic Regression 1:18:13 Classification Report Confusion Metrix 1:28:51 Logistic Regression Multiclass Classification 1:41:29 Data Cleaning and Preparation 2:10:23 SVM 2:41:02 Overfitting Underfitting 2:54:29 Bias Variance 3:00:21 Decision Tree 3:18:11 Random Forest 3:30:26 Cross Validation 3:51:07 Grid Search CV 4:01:59 Ensemble Learning Bagging Boosting 4:08:59 Unsupervised Learning 4:14:39 K Means 4:27:50 Capstone Project Do you want to learn technology from me? Check https://codebasics.io/?utm_source=description&utm_medium=yt&utm_campaign=description&utm_id=description for my affordable video courses. Need help building software or data analytics/AI solutions? My company https://www.atliq.com/ can help. Click on the Contact button on that website. 🎥 Codebasics Hindi channel: https://www.youtube.com/channel/UCTmFBhuhMibVoSfYom1uXEg #️⃣ Social Media #️⃣ 🧑🤝🧑 Discord for Community Support: https://discord.gg/r42Kbuk 🏫 Skool Community for Support & Networking - https://resources.codebasics.io/6J8mXg 📸 Codebasics' Instagram: https://www.instagram.com/codebasicshub/ 📝 Codebasics' Linkedin : https://www.linkedin.com/company/codebasics/ 📱 Dhaval's X handle : https://x.com/dpcodebasics ------ 📝 Dhaval's Linkedin : https://www.linkedin.com/in/dhavalsays/ 📝 Hem's Linkedin: https://www.linkedin.com/in/hemvad/ 📽️ Hem's Instagram for daily tips: https://www.instagram.com/hemvadivel/ 📸 Dhaval's Personal Instagram: https://www.instagram.com/dhavalcodebasics 🔗 Patreon: https://www.patreon.com/codebasics?fan_landing=true
