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An Introduction to Scikit-Learn

Your one stop shop for getting familiar with Scikit-Learn, one of the most important modelling packages in Python.
4.9
4.9/5
(9 reviews)
25 students
Created by

8.9

CourseMarks Score®

8.7

Freshness

10.0

Feedback

7.4

Content

Platform: Udemy
Video: 1h 13m
Language: English
Next start: On Demand

Top Scikit-learn courses:

Detailed Analysis

CourseMarks Score®

8.9 / 10

CourseMarks Score® helps students to find the best classes. We aggregate 18 factors, including freshness, student feedback and content diversity.

Freshness Score

8.7 / 10
This course was last updated on 12/2020.

Course content can become outdated quite quickly. After analysing 71,530 courses, we found that the highest rated courses are updated every year. If a course has not been updated for more than 2 years, you should carefully evaluate the course before enrolling.

Student Feedback

10.0 / 10
We analyzed factors such as the rating (4.9/5) and the ratio between the number of reviews and the number of students, which is a great signal of student commitment.

New courses are hard to evaluate because there are no or just a few student ratings, but Student Feedback Score helps you find great courses even with fewer reviews.

Content Score

7.4 / 10
Video Score: 7.7 / 10
The course includes 1h 13m video content. Courses with more videos usually have a higher average rating. We have found that the sweet spot is 16 hours of video, which is long enough to teach a topic comprehensively, but not overwhelming. Courses over 16 hours of video gets the maximum score.
The average video length is 4 hours 17 minutes of 4 Scikit-learn courses on Udemy.
Detail Score: 9.0 / 10

The top online course contains a detailed description of the course, what you will learn and also a detailed description about the instructor.

Extra Content Score: 5.5 / 10

Tests, exercises, articles and other resources help students to better understand and deepen their understanding of the topic.

This course contains:

0 article.
0 resource.
0 exercise.
0 test.

Table of contents

Description

This course will cover the theory behind many key concepts in the model building workflow. We will look at how to preprocess data and then how to use sklearn to run a series of models, including Regressions, Suport Vector Machines, Neural Networks and Hierarchical Clustering methods. We will also discuss how to evaluate models for their performance and improve them through Cross Validation and Hyperparameter Tuning.

You will learn

✓ This course is a one stop shop for an introduction to sklearn, the most commonly used Python package for statistical modelling
✓ This course will cover all aspects of the modelling workflow.
✓ We will look at Preprocessing, running Regressions, Classifications, Neural Networks and Clustering algorithms
✓ We will also cover Evaluation methodology for building highly successful models

Requirements

• The only requirement is a basic understanding of Python

This course is for

• Beginner Python developers with an interest in running Python statistical models.

How much does the An Introduction to Scikit-Learn course cost? Is it worth it?

The course costs $14.99. And currently there is a 25% discount on the original price of the course, which was $19.99. So you save $5 if you enroll the course now.
The average price is $12.2 of 4 Scikit-learn courses on Udemy.

Does the An Introduction to Scikit-Learn course have a money back guarantee or refund policy?

YES, An Introduction to Scikit-Learn has a 30-day money back guarantee. The 30-day refund policy is designed to allow students to study without risk.

Are there any SCHOLARSHIPS for this course?

Currently we could not find a scholarship for the An Introduction to Scikit-Learn course, but there is a $5 discount from the original price ($19.99). So the current price is just $14.99.

Who is the instructor? Is Dhruva Krishna a SCAM or a TRUSTED instructor?

Dhruva Krishna has created 1 courses that got 9 reviews which are generally positive. Dhruva Krishna has taught 25 students and received a 4.9 average review out of 9 reviews. Depending on the information available, Dhruva Krishna is a TRUSTED instructor.
Data Scientist
I am a Data Scientist with experience in Trading, IoT and Sports Analytics sectors. I have spent considerable time understanding Machine Learning models, both in Python and on a theoretical level and building complex visualisations in BI tools such as Tableau.

I have been responsible for building high speed trading algorithms in the foreign exchange and commodities markets, both from a technical and fundamental analysis perspective. I also have built statistical modelling tools in Sports Analysis, for both the Betting markets and Behavioural Analysis sector.

8.9

CourseMarks Score®

8.7

Freshness

10.0

Feedback

7.4

Content

Platform: Udemy
Video: 1h 13m
Language: English
Next start: On Demand

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