Chevron Left
返回到 Supervised Machine Learning: Regression and Classification

学生对 DeepLearning.AI 提供的 Supervised Machine Learning: Regression and Classification 的评价和反馈

4.9
31,304 个评分

课程概述

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....

热门审阅

MA

Jan 27, 2025

I've really enjoyed learning about Machine Learning in such a guided way. It will continue to inspire me to learn more about AI. Thank you Andrew Ng, DeepLearning.AI, Standford ONLINE, and Coursera.

AP

Sep 3, 2022

A​ perfect course for beginners who are seeking to learn machine learning. I want to thank Mr. Andrew Ng and his team for this wonderful course. Thank you so much for providing this quality course.

筛选依据:

1676 - Supervised Machine Learning: Regression and Classification 的 1700 个评论(共 5,926 个)

创建者 Ali S

Jul 16, 2022

Complete materials/explanations on machine learning fundamentals.

An enjoyable course to participate.

Thanks Dr. Ng

创建者 Dean C

Jun 9, 2025

Very beginner friendly. I breezed through it, without any formal qualifications in mathematics. Very well explained.

创建者 Patrick W O B

May 11, 2025

Very engaging and exemplary that I have learned things that I have not been able to even absorb when I'm in college.

创建者 Karthi M

Feb 16, 2025

Excellent course for beginners, an unique point is duration of videos are cleverly designed to make it more engaging

创建者 Muhaned M

Feb 4, 2025

the cousre is very good but as a coder and ML ENG we needed scikit learn code to be learned and explained , thanks !

创建者 Abdullah N

Sep 20, 2024

well organized material with great quality, loved the step by step approach combined with quizzes and code examples.

创建者 He H

Aug 13, 2024

Good for a starter, I learned the ML concepts before and it also gives me a better understanding of the ML structure

创建者 Adnan R

Jun 27, 2024

Very well structured course. Content was exceptional and the way coursera interface drive the course is exceptional.

创建者 Vansh C

Apr 21, 2024

I have never seen such amount of attention to detail in any course. This course enables me to make quality projects.

创建者 Gregory G

Feb 8, 2024

Excellent explanation and pace. I liked the optional labs and deeper explanations of the math behind the algorithms

创建者 Chirayu R

Jan 22, 2024

The course was good. But the thing that really made me confuse is the unnecessary code in the last weeks assignment.

创建者 Omar E

Aug 30, 2023

Great for entry level with focus on understanding of concepts and getting the big picture behind the science itself.

创建者 Yamoo T

Nov 27, 2022

This course is great and it a definitely suitable course that is prepared for beginners. Everyone should learn it!!!

创建者 Barath U

Sep 25, 2022

It is a wonderful journew with Supervised Machine learning, I am so greatful to take this ML Specialization course.

创建者 Pooria r

Sep 10, 2022

With all my heart and honestly, I can say that it was the best course I saw thanks a lot I appreciate it very much

创建者 Muhammad S

Jul 25, 2022

Best course on supervised machine learning by one of the best instructors. It is nither too simple nor too complex.

创建者 Michelle S

Jul 24, 2022

Excelent. The interactive examples in python make it easier to understand. Congratulations for this excelent course.

创建者 zhifine

Aug 1, 2024

I like this course very much! It help me go through the basic concept of machine learning quickly, It is wonderful!

创建者 Rishipramod C

Jul 13, 2024

I personally says it is a fantastic journey throughout my course and learnt a lot new things...Thank you sir....!!!

创建者 TERAN C E A

Jun 30, 2024

Excelentes explicaciones y metodologías. El instructor sabe cómo transmitir conceptos complejos de manera sencilla.

创建者 Santosh R

May 13, 2024

i dont have words to express my gratitude to professor Andrew Ng. This is the best course I have ever taken online.

创建者 Paolo B

Nov 23, 2023

Great teacher, great knowledge. Also very engaging and totally not boring. I wish to have all courses at this level

创建者 Mark E

Oct 12, 2023

Just the right balance of learning intuition, formal mathematics and coding to get my feet wet in machine learning.

创建者 Sameer M

Jul 31, 2023

I have learnt more in this course than my 4 year degree. Thank you Andrew NG and coursera for making this possible.

创建者 June C

Jul 14, 2023

The instructor is really inspiring. The talk with another great machine learning scientist Fei-fei is also amazing!