Supervised Machine Learning for beginners

Supervised Machine Learning for beginners, available at $44.99, has an average rating of 4.15, with 23 lectures, based on 50 reviews, and has 174 subscribers.

You will learn about scikit-learn machine learning artificial intelligence jupyter python supervised learning regression classification data processing model training model evaluation hands-on experience This course is ideal for individuals who are Beginner in machine learning It is particularly useful for Beginner in machine learning.

Enroll now: Supervised Machine Learning for beginners

Summary

Title: Supervised Machine Learning for beginners

Price: $44.99

Average Rating: 4.15

Number of Lectures: 23

Number of Published Lectures: 23

Number of Curriculum Items: 23

Number of Published Curriculum Objects: 23

Original Price: $24.99

Quality Status: approved

Status: Live

What You Will Learn

scikit-learn
machine learning
artificial intelligence
jupyter
python
supervised learning
regression
classification
data processing
model training
model evaluation
hands-on experience

Who Should Attend

Beginner in machine learning

Target Audiences

Beginner in machine learning

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!

Course Curriculum

Chapter 1: Introduction

Lecture 1: Greetings!

Lecture 2: Jupyter

Lecture 3: Supervised learning

Chapter 2: Classification problems

Lecture 1: Binary classification

Lecture 2: Multiclass classification

Lecture 3: Regression

Chapter 3: Data analysis and preparation

Lecture 1: Categorical data

Lecture 2: Scaling

Lecture 3: Standardization

Lecture 4: Splitting data

Chapter 4: Model testing and evaluation

Lecture 1: Accuracy

Lecture 2: Confusion Matrix

Lecture 3: Precision and Recall

Lecture 4: Root mean square error

Chapter 5: Linear models

Lecture 1: Linear regression

Lecture 2: Logistic regression

Chapter 6: K nearest neighbors

Lecture 1: KNN for classification

Lecture 2: KNN for regression

Chapter 7: Decision trees and random forests

Lecture 1: Trees for classification

Lecture 2: Trees for regression

Lecture 3: Random forests

Chapter 8: Conclusion

Lecture 1: Conclusion and next steps

Chapter 9: Appendix

Lecture 1: Appendix A

Instructors

Ro Science
Data Science and Machine Learning

Rating Distribution

1 stars: 0 votes
2 stars: 1 votes
3 stars: 10 votes
4 stars: 20 votes
5 stars: 19 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

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