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Step into the world of Machine Learning with this ultimate roadmap that takes you from the basics of Python and Pandas to mastering advanced ML algorithms! This course begins with essential Python and Data Science libraries like Matplotlib for visualization, then dives deep into Regression, Classification, and Clustering techniques. Learn how Linear and Logistic Regression work, understand evaluation metrics, VIF, and Sigmoid functions, and build practical projects using Decision Trees, Random Forests, and K-Means Clustering. Through hands-on examples such as the Spam Email Classifier, you’ll gain real-world experience in data preprocessing, model building, and hyperparameter tuning. By the end, you’ll not only understand the theory but also know how to apply ML in real-world scenarios, making you job-ready for 2026! Below are the topics covered in Machine Learning Course For Beginners 00:00:00 – Introduction to Machine Learning Course 00:00:56 – Python for Data Science 00:03:57 – Pandas for Data Science 01:10:00 – Data Visualization with Matplotlib 02:02:24 – Machine Learning Around You 02:09:08 – Introduction to Machine Learning 02:29:33 – Machine Learning Myths 02:43:02 – Types of Machine Learning 02:58:05 – What You Can Do with Machine Learning 03:04:08 – What is Regression? 03:13:40 – Types of Regression 03:15:25 – What is Linear Regression? 03:45:41 – Evaluation Metrics 03:56:38 – Variance Inflation Factor (VIF) 04:01:28 – VIF Formula 04:11:34 – Linear Regression Hands-on 05:07:29 – Machine Learning Intro (Recap) 05:08:00 – Introduction to Logistic Regression 05:27:43 – What is Logistic Regression? 05:31:07 – Example: Spam Email Classifier 05:31:33 – Step 01: Independent Variables & Common Spam Words 05:33:31 – Step 02: Probability 05:40:08 – Understanding Log(Odds) 05:44:28 – Sigmoid Function 05:47:55 – Individual Likelihood & Log(Likelihood) 05:49:44 – What Does Log(Odds) Mean? 05:50:55 – What Does Sigmoid Function Mean? 06:10:00 – Maximum Likelihood Estimate 06:20:12 – Step 04: Likelihood of Data 07:09:14 – Logistic Regression Hands-on 07:10:14 – Label Encoding / One Hot Encoding 07:21:54 – Decision Tree 07:36:30 – Random Forest 07:49:32 – Theory of Decision Tree 07:51:54 – Decision Tree Terminology 08:09:34 – Theory of Random Forest 08:26:32 – Important Hyperparameters in Random Forest 08:37:45 – Hands-on: Random Forest 09:00:12 – Data Visualization 09:03:05 – Model Building 09:08:23 – Hyperparameter Tuning 09:24:00 – Model Evaluation 09:29:31 – K-Means Clustering 10:24:42 – ML IQ #machinelearningcourse #machinelearningfullcourse #machinelearningtutorial #intellipaat 🔥Enroll for Intellipaat's Machine Learning Course: https://intellipaat.com/machine-learning-certification-training-course/ ➡️ About the Course Gain expertise in Artificial intelligence and Machine Learning through an Executive Post Graduate Certification program in AI and ML offered by iHUB DivyaSampark, a Technology Innovation Hub of IIT Roorkee, in collaboration with Intellipaat This AI and ML program is in collaboration with tech giants Microsoft. Get classes and guidance directly from IIT Faculty and industry experts, with personalized 1:1 mentorship. Become IIT certified AI and ML expert with this online BootCamp. 📌 Do subscribe to Intellipaat channel & come across more relevant Tech content: https://goo.gl/hhsGWb ▶️ Intellipaat Achievers Channel: https://www.youtube.com/@intellipaatachievers 📚For more information, please write back to us at [email protected] or call us at IND: +91-7022374614 / US : 1-800-216-8930
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