Chevron Left
Back to Supervised Machine Learning: Regression and Classification

Learner Reviews & Feedback for Supervised Machine Learning: Regression and Classification by DeepLearning.AI

4.9
stars
22,170 ratings

About the Course

In the first course of the Machine Learning Specialization, you will: • Build machine learning models in Python using popular machine learning libraries NumPy and scikit-learn. • Build and train supervised machine learning models for prediction and binary classification tasks, including linear regression and logistic regression The Machine Learning Specialization is a foundational online program created in collaboration between DeepLearning.AI and Stanford Online. In this beginner-friendly program, you will learn the fundamentals of machine learning and how to use these techniques to build real-world AI applications. This Specialization is taught by Andrew Ng, an AI visionary who has led critical research at Stanford University and groundbreaking work at Google Brain, Baidu, and Landing.AI to advance the AI field. This 3-course Specialization is an updated and expanded version of Andrew’s pioneering Machine Learning course, rated 4.9 out of 5 and taken by over 4.8 million learners since it launched in 2012. It provides a broad introduction to modern machine learning, including supervised learning (multiple linear regression, logistic regression, neural networks, and decision trees), unsupervised learning (clustering, dimensionality reduction, recommender systems), and some of the best practices used in Silicon Valley for artificial intelligence and machine learning innovation (evaluating and tuning models, taking a data-centric approach to improving performance, and more.) By the end of this Specialization, you will have mastered key concepts and gained the practical know-how to quickly and powerfully apply machine learning to challenging real-world problems. If you’re looking to break into AI or build a career in machine learning, the new Machine Learning Specialization is the best place to start....

Top reviews

JM

Invalid date

Specacular course to learn the basics of ML. I was able to do it thanks to finnancial aid and I'm very grateful because this was really a great oportunity to learn. Looking forward to the next courses

AD

Invalid date

Amazingly delivered course! Very impressed. The concepts are communicated very clearly and concisely, making the course content very accessible to those without a maths or computer science background.

Filter by:

4526 - 4537 of 4,537 Reviews for Supervised Machine Learning: Regression and Classification

By Patricia R

•

Oct 20, 2023

Me paso lo mismo con el curso anterior y es que si no realizas los laboratorios aunque hayas aprobado todo y a pesar de que los test te dan como aprobados dicen que no apruebas y que quedas en 0%, es algo como reiterativo con coursera asi que me rindo, no continuo intentando sacarme certificados por acá

By DV B

•

Jun 20, 2024

Mostly I was inundated with Nagware after ever short video segment, only to discover that Machine Learning learning was not even introduced. Wasted much time on trivialities like linear regression. I never learned anything about Machine Learning, per se.

By Muhammad T C

•

Feb 17, 2024

Although i can see that the next course is included in my learning program but i can not progress in it because the system keeps on asking me to pay for the course.

By andualem c

•

May 19, 2024

I'm very excited to move to the next level of this field i after i took this foundational courses. It is well organized and very engaging course.

By Elijah G

•

May 15, 2024

This course is not for beginners. If you are not already familiar with programming and advanced math don't waste your time.

By Halyna D

•

Aug 12, 2024

Absolutely not worthen this money. This course is suitable only for non-technical people without any experience in ML/DS.

By Samantha C

•

Jun 27, 2024

They don't provide slides, so there's not way to take notes or go back and reference material.

By John J C E

•

Aug 11, 2024

too many failures and lack of troubleshooting support in the labs

By Emek T

•

Jul 5, 2024

Too much math, not enough practical code examples

By nouhaila a

•

May 1, 2024

I can't see my certification

By Abdullah A

•

Aug 15, 2024

Jupyter Lab doesn't work.