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Random Forest Model using Python

Instructor:

Mr. Anirudh Rao
Beginner

Level

1.5 Hrs

Learning hours

640

Learners

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About this Live Session

Great Learning brings you this live session on “Random Forest Model Using Python”. The random forest algorithm is one of the most popular and commonly used algorithms in the field of Machine Learning. Since it is an ensemble model, the accuracy of random forest models is much better than simple algorithms. The best part of a random forest algorithm is that it can be used for both classification as well as regression problems, and you can be assured of the fact that the accuracy of the models would be great in both the cases. In this session, we will comprehensively understand the concept of random forest model and will dive into the mathematics underlying it, post which we will head onto the demonstration part, where we will be implementing the random forest algorithm using Python. Here we will be using Scikit-Learn library to build the RF model. Finally, there will be a QnA session, where all your queries and suggestions would be discussed.

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Random Forest Model using Python

1.5 Hrs

Learning hours

Beginner

Level

640

Learners

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Our instructor

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Mr. Anirudh Rao

Data Science Expert

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115.6K+ Learners
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30 Courses
Anirudh has been working in the field of Data Science and has expertise over Python, Machine Learning and other concepts in the field of data analysis. He is also proficient in the concept of Deep Learning and its usage in a production environment. Expertise extends towards working on various projects in the domain of Artificial Intelligence and Neural Networks as well.

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