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Welcome to this informative video on Machine Learning Course! In this video, we will delve into the fascinating world of machine learning.

In this video, we will explore various machine learning techniques, including linear regression using Python, multiple linear regression, logistic regression, and the Naive Bayes Classifier. We will also discuss entropy and SMOTE, and the advantages and disadvantages of decision trees.

Data preprocessing is an essential step in machine learning, and we will cover its significance and techniques. We will also discuss unsupervised learning techniques such as K-means and hierarchical clustering and the Silhouette score.

Finally, we will discuss some common machine-learning interview questions to help you prepare for your next machine-learning interview.

So, sit back, relax, and join us on this exciting journey through the world of machine learning. Don't forget to subscribe to our channel for more informative content on machine learning and artificial intelligence.

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Intellipaat is a global online professional training provider. We are offering some of the most updated, industry-designed certification training programs which include courses in Big Data, Data Science, Artificial Intelligence, and 150 other top-trending technologies.
We help professionals make the right career decisions, choose trainers with over a decade of industry experience, provide extensive hands-on projects, rigorously evaluate learner progress, and offer industry-recognized certifications. We also assist corporate clients in upskilling their workforce and keeping them in sync with the changing technology and digital landscape.

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🔵 Here is a breakdown of the topics covered in the video:

➡️ 00:00:00 - Introduction
➡️ 00:05:34 - Basics of Machine Learning
What it is?
How it's changing the world around us?

➡️ 00:30:56 - Various Types of Machine Learning
Supervised
Unsupervised
Reinforcement Learning

➡️ 00:54:49 - Regression using Python
Linear Regression
Logistic Regression

➡️ 02:57:02 - Explore these concepts in Detail
How to Implement Them in Code?
The Mathematical Concepts behind them

➡️ 05:31:38 - Entropy
A measure of Uncertainty in a system

➡️ 05:44:36 - Smote
An Oversampling technique used to address the class imbalance in datasets

➡️ 05:47:34 - Disadvantages of Decision Trees

➡️ 07:02:45 - Naive Bayes Classifier
An algorithm used for Classification Tasks
Unsupervised Learning Techniques like K-means
Hierarchical Clustering

➡️ 09:14:54 - Silhouette Score
A metric used to Evaluate the Performance of Clustering Algorithms

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