Explore the fundamentals of machine learning algorithms in this comprehensive 1-hour 17-minute video tutorial. Delve into the importance of machine learning in today's technological landscape and its future applications. Gain a solid understanding of key concepts, including the different types of machine learning and how models learn. Discover the practical applications of popular algorithms such as Linear Regression, Naive Bayes, K-Nearest Neighbors (KNN), Support Vector Machines, and Random Forest. Learn how Python is utilized in machine learning and get insights into the theoretical and practical aspects of these algorithms. By the end of this tutorial, develop a strong foundation in machine learning concepts and their real-world applications.
Overview
Syllabus
Introduction.
Agenda.
Introduction to Machine Learning.
Why is Machine Learning required?.
Types of Machine Learning.
How does a Machine Learning model learn?.
Python for Machine Learning.
Machine Learning algorithms.
Linear Regression.
Naive Bayes algorithm.
KNN algorithm.
Support Vector Machines.
Random Forest algorithm.
Summary.
Taught by
Great Learning
