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Machine Learning Foundations: A Case Study Approach

Do you have data and wonder what it can tell you? Do you need a deeper understanding of the core ways in which machine learning can improve your business? ...
4.6
4.6/5
(12,494 reviews)
340,595 students
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9.0

CourseMarks Score®

N/A

Freshness

8.4

Feedback

9.1

Content

Platform: Coursera
Price: $0
Video: 8h 38m
Language: English

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Detailed Analysis

CourseMarks Score®

9.0 / 10

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8.4 / 10
We analyzed factors such as the rating (4.6/5) 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

9.1 / 10
Video Score: 8.9 / 10
The course includes 8h 38m 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.
Detail Score: 8.4 / 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: 9.8 / 10

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

This course contains:

25 articles.
0 resource.
0 exercise.
11 tests or quizzes.

Table of contents

Description

Do you have data and wonder what it can tell you? Do you need a deeper understanding of the core ways in which machine learning can improve your business? Do you want to be able to converse with specialists about anything from regression and classification to deep learning and recommender systems?

In this course, you will get hands-on experience with machine learning from a series of practical case-studies. At the end of the first course you will have studied how to predict house prices based on house-level features, analyze sentiment from user reviews, retrieve documents of interest, recommend products, and search for images. Through hands-on practice with these use cases, you will be able to apply machine learning methods in a wide range of domains.

This first course treats the machine learning method as a black box. Using this abstraction, you will focus on understanding tasks of interest, matching these tasks to machine learning tools, and assessing the quality of the output. In subsequent courses, you will delve into the components of this black box by examining models and algorithms. Together, these pieces form the machine learning pipeline, which you will use in developing intelligent applications.

Learning Outcomes: By the end of this course, you will be able to:
-Identify potential applications of machine learning in practice.
-Describe the core differences in analyses enabled by regression, classification, and clustering.
-Select the appropriate machine learning task for a potential application.
-Apply regression, classification, clustering, retrieval, recommender systems, and deep learning.
-Represent your data as features to serve as input to machine learning models.
-Assess the model quality in terms of relevant error metrics for each task.
-Utilize a dataset to fit a model to analyze new data.
-Build an end-to-end application that uses machine learning at its core.
-Implement these techniques in Python.

You will learn

Requirements

The course creator has not defined the requirements for this course.

This course is for

The course creator hasn’t defined the level of this course.

How much does the Machine Learning Foundations: A Case Study Approach course cost? Is it worth it?

Access to most course materials is FREE in audit mode on Coursera. If you wish to earn a certificate and access graded assignments, you must purchase the certificate experience during or after your audit.

If the course does not offer the audit option, you can still take a free 7-day trial.

Does the Machine Learning Foundations: A Case Study Approach course have a money back guarantee or refund policy?

Coursera offers a 7-day free trial for subscribers.

Are there any SCHOLARSHIPS for this course?

YES, you can get a scholarship or Financial Aid for Coursera courses. The first step is to fill out an application about your educational background, career goals, and financial circumstances. Learn more about financial aid on Coursera.

Who is the instructor? Is Emily Fox a SCAM or a TRUSTED instructor?

Emily Fox has created 6 courses that got 931 reviews which are generally positive. Emily Fox has taught 413241 students and received a 4.7 average review out of 931 reviews. Depending on the information available, Emily Fox is a TRUSTED instructor.
Statistics
University of Washington
Emily Fox is an assistant professor and the Amazon Professor of Machine Learning in the Statistics Department at the University of Washington. She was formerly at the Wharton Statistics Department at the University of Pennsylvania. Emily is a recipient of the Sloan Research Fellowship, a US Office of Naval Research Young Investigator award, and a National Science Foundation CAREER award. Her research interests are in large-scale Bayesian dynamic modeling and computations.

9.0

CourseMarks Score®

N/A

Freshness

8.4

Feedback

9.1

Content

Platform: Coursera
Price: $0
Video: 8h 38m
Language: English

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