What Is Supervised Learning In Machine Learning? | Machine Learning For Beginners | Simplilearn

This video on What is Supervised Learning in machine learning will take you through a detailed concept of Supervised Learning. This video will help you to understand What is Machine Learning, what is supervised learning, how supervised learning works, the advantages and disadvantages of supervised learning, what are the types of supervised learning - classification, regression, supervised learning algorithms, and applications of supervised learning.

01:26 What is Machine Learning?
Machine learning is the art of making computers learn and act like humans by feeding data and which focuses on the utilization of information and imitating the way that people learn, step by step working on its accuracy.

02:05 What is Supervised Learning?
In supervised machine learning, machines are trained using labeled data also known as training data to predict results. Here, labeled data refers to a group of data that have been tagged with one or more names, and the data is already known to the machine.

03:30 Advantages of Supervised Learning
Real-world computation problems
Optimization
Prediction
Reusable data

04:22 Disadvantages of Supervised Learning
Computation time
Updates
Pre-Processing data

04:54 Types of supervised machine learning
Classification
Regression

05:04 Classification- Classification is a process in which new observations are recognized, and separated in such a way that they can be categorized.

05:46 Regression- A regression algorithm is used to figure out the connection between dependent and independent variables.

07:00 supervised learning Algorithms

Linear regression
Regression trees
Non-linear regression
Bayesian Linear Regression
Random Forest
Decision Trees
Logistic Regression
Support Vector Machine

11:07 Applications of Supervised Learning

Image and object recognition
Predictive analysis
Customer Sentiment analysis
Spam detection


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