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Learner Reviews & Feedback for Build Regression, Classification, and Clustering Models by CertNexus

4.2
stars
10 ratings

About the Course

In most cases, the ultimate goal of a machine learning project is to produce a model. Models make decisions, predictions—anything that can help the business understand itself, its customers, and its environment better than a human could. Models are constructed using algorithms, and in the world of machine learning, there are many different algorithms to choose from. You need to know how to select the best algorithm for a given job, and how to use that algorithm to produce a working model that provides value to the business. This third course within the Certified Artificial Intelligence Practitioner (CAIP) professional certificate introduces you to some of the major machine learning algorithms that are used to solve the two most common supervised problems: regression and classification, and one of the most common unsupervised problems: clustering. You'll build multiple models to address each of these problems using the machine learning workflow you learned about in the previous course. Ultimately, this course begins a technical exploration of the various machine learning algorithms and how they can be used to build problem-solving models....
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1 - 2 of 2 Reviews for Build Regression, Classification, and Clustering Models

By Anna t B

•

May 17, 2021

Course content was well curated, however, the peer grading took much longer than any other course I've taken on Coursera leaving me with open courses that charged me more money instead of acknowledging the work had been completed and letting me complete the course. Just exists to make money, do not take this course if you have a deadline or a budget, expect to not get a peer graded review or grade for several days or weeks. Without that grade, you cannot complete the course, let alone the certificate.

By Ms M A H

•

Jun 27, 2022

Course refused to let me progress beyond Week 1. No reason given. I audited this course - I am so glad that I paid nothing if the course is not going to deliver the full information.