The 10 Best Machine Learning Algorithms for Data Science Beginners

Link : The 10 Best Machine Learning Algorithms for Data Science Beginners

Without Further Ado, The Top 10 Machine Learning Algorithms for Beginners:
Linear Regression. In machine learning, we have a set of input variables (x) that are used to determine an output variable (y). ...
Logistic Regression. ...
CART. ...
Naïve Bayes. ...
KNN. NEW
The 10 Best Machine Learning Algorithms for Data Science Beginners

4.6 (3 ratings)
4 students enrolled
Created by Ro Science

What you'll learn


  • scikit-learn
  • machine learning
  • artificial intelligence
  • jupyter
  • python
  • supervised learning

Requirements


  • basic coding

If you are a developer, an architect, an engineer, a techie, a computer enthusiast or just remotely in IT, if you are interested in taking on machine learning but you are not too sure where to start, this could be the right course for you..

In this course, we start with the basics and we explain the concept of supervised learning in depth, we also go over the various types of problems that can be solved using supervised learning techniques. Then we get more hands-on and use simple bits of code to illustrate some concepts relative to data preparation and model evaluation. And last, we actually train and evaluate several models based on some of the most common machine learning algorithms for supervised learning such as K-nearest neighbors, logistic regression, decision trees and random forests.

I hope that this course gives you a good overview of supervised learning and helps kick start your machine learning journey!

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