Supervised Machine Learning for beginners
- 4.7
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Brief Introduction
kick start your machine learning journey with supervised learning for beginners, python, jupyter and scikit-learn!Description
If you are a developer, an architect, an engineer, a techie, an IT enthusiast, a student or just a curious person, if you are interested in taking on machine learning but you are not too sure where to start, this is probably 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 illustrate some concepts relative to data preparation and model evaluation with bits of code that you can easily reuse. And last, we actually train and evaluate several models based on the most common machine learning algorithms for supervised learning such as K-nearest neighbors, logistic regression, decision trees and random forests.
I hope that you find this course fun and easy to follow and that it gives you the machine learning background you need to kick start your journey and be successful in this field!
Requirements
- Requirements
- basic coding
Knowledge
- scikit-learn
- machine learning
- artificial intelligence
- jupyter
- python
- supervised learning
- regression
- classification
- data processing
- model training
- model evaluation
- hands-on experience
Ro Science
4.7 Raiting
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