Dive into the world of Machine Learning with this complete beginner-friendly course by Intellipaat! Whether you’re just starting your data science journey or looking to solidify your understanding of ML fundamentals, this course has everything you need. You’ll begin with Python and Pandas for data analysis, followed by Matplotlib for creating powerful data visualizations. Once your foundation is set, we’ll guide you into the core of Machine Learning – covering real-world applications, debunking common myths, and exploring the different types of learning models.
From regression basics to advanced topics like Variance Inflation Factor (VIF), this course provides a thorough walkthrough of Linear and Logistic Regression, complete with step-by-step hands-on projects. You’ll build spam classifiers, learn the math behind sigmoid functions, and master evaluation metrics like Log(Odds) and Maximum Likelihood Estimates. As the course progresses, you’ll explore essential algorithms like Decision Trees, Random Forest, and K-Means Clustering, along with model building, encoding, hyperparameter tuning, and performance evaluation. Packed with theory, practical examples, and real-world projects, this course will equip you with the skills to confidently tackle ML challenges and prepare for a successful career in data science and AI.
Below are the topics covered in Machine Learning Course For Beginners
00:00:00 – Introduction to Machine Learning Course
00:01:05 – Python for Data Science
00:04:06 – Pandas for Data Science
01:10:09 – 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
Section 3: Linear Regression Advanced
03:56:38 – Variance Inflation Factor (VIF)
04:01:28 – VIF Formula
04:11:34 – Linear Regression Hands-on
05:07:29 – Introduction to Machine Learning
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 Variable & Common Spam Words
05:33:31 – Step 02: Probability
05:40:08 – Log(Odds)
05:44:28 – Sigmoid Function
05:47:55 – Individual Likelihood and 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
09:29:40 – K-Means Clustering
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🔥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.
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