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学生对 IBM 提供的 使用 Python 进行机器学习 的评价和反馈

4.7
8,856 个评分
1,404 条评论

课程概述

This course dives into the basics of machine learning using an approachable, and well-known programming language, Python. In this course, we will be reviewing two main components: First, you will be learning about the purpose of Machine Learning and where it applies to the real world. Second, you will get a general overview of Machine Learning topics such as supervised vs unsupervised learning, model evaluation, and Machine Learning algorithms. In this course, you practice with real-life examples of Machine learning and see how it affects society in ways you may not have guessed! By just putting in a few hours a week for the next few weeks, this is what you’ll get. 1) New skills to add to your resume, such as regression, classification, clustering, sci-kit learn and SciPy 2) New projects that you can add to your portfolio, including cancer detection, predicting economic trends, predicting customer churn, recommendation engines, and many more. 3) And a certificate in machine learning to prove your competency, and share it anywhere you like online or offline, such as LinkedIn profiles and social media. If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge upon successful completion of the course....

热门审阅

RC

Feb 07, 2019

The course was highly informative and very well presented. It was very easier to follow. Many complicated concepts were clearly explained. It improved my confidence with respect to programming skills.

RN

May 26, 2020

Labs were incredibly useful as a practical learning tool which therefore helped in the final assignment! I wouldn't have done well in the final assignment without it together with the lecture videos!

筛选依据:

126 - 使用 Python 进行机器学习 的 150 个评论(共 1,394 个)

创建者 kim n

Jun 01, 2020

Machine learning is not easy subject, but this intermediate level course covers enough for the its target.

The strong part is belong to lab work and final assignment. They are real work with repetition helps to remember the theory and get skills.

创建者 Dhananjayan P N

May 21, 2020

Great Course! Before taking this course, the idea of Machine Learning was very unclear. After successfully completing this course, I know it all. I highly recommend this course for anyone looking to understand Machine Learning along with Python.

创建者 Magnus B

Feb 07, 2019

I really enjoyed the course and was happy to find that the information provided was broken down enough to make it simple to understand the concepts. The labs were helpful and the final project was a nice gauge of what I needed to improve on.

创建者 AVIJIT B

Apr 11, 2020

The course is good for someone who has some knowledge of machine learning. Teaches you many new things. Overall i good learning experience. I would suggest this course to the ones, who wants their career in data analyst or data scientist.

创建者 Niamh K

Jul 01, 2020

Awesome course fantastically set out. I feel like it covered a huge range of topics from some nice introductory stuff up to really great advanced techniques. It's given me a lot to think about and work on in the future! Thanks very much.

创建者 KIRAN V T

May 04, 2020

This is one of the best machine learning courses i have taken with good practicals and nice examples. Moreover the instructor was good and has a funny way of talking which i enjoyed. Overall a full score worthy course. Keep it up IBM!!

创建者 Oksana Z

Jun 06, 2020

This course is exceptional in IBM Data Science Professional Certificate Program. It provides newcomers with the ready-to-use tools in machine learning. I especially liked the part on recommendation systems and wish it had more content!

创建者 Abhijit H J

Dec 15, 2019

The course was awesome, I got a good understanding of the ML algorithms. If the explanation would have been along with the python code, then it would have been better for understanding.

But still, I must say the course was just awesome.

创建者 Jafed E

Jul 06, 2019

I enjoy the lectures. The professor has a good speaking and teaching style which keeps me interested. Lots of concrete math examples which make it easier to understand. Very good slides which are well formulated and easy to understand

创建者 Rupam H

Jun 16, 2020

Gone through so many courses but didn't find like this before. This course is too good. As an intermediate, I can say that this course described very complex topics in such a easy way making it very much understandable for beginners.

创建者 Chandan K S

Apr 26, 2020

For absolute beginners, this course is really amazing. If anyone don't know anything or any algorithms of machine learning. Then this course is for them. So, i would like to say for beginners this course is really amazing. Thank you!

创建者 YASH G

Feb 18, 2020

The course was helpful and the final assignment was very good. You have to go through all of the concepts again. But it would be great if assignments would be different for everyone, then validating part would be interesting as well.

创建者 ONG K S

Nov 13, 2019

Awesome machine learning course. Unlike most of other courses which come with technical mathematic jargon, this course explain everything in laymen term. Even myself without in depth knowledge in maths can understand it. Well done.

创建者 Omid C

Feb 27, 2020

The course provides an excellent overview of some essential algorithms in the field of Machine Learning. The instructor has the ability to explain the core idea of each algorithm in an intuitive way. I liked the course so much :)

创建者 Nazmus S S

Apr 08, 2020

This course is awesome in one word. This course is great for learning the classification algorithms in such an ease with all the power these algorithms possess. I loved the way instructor SAEED AGHABOZORGI instructed the course.

创建者 Ashish B

Feb 02, 2020

This is a very informative course. The content is amazingly put together. Not only is this course rich in concepts of Machine Learning, but it is also robust in the implementation of ML with Python. This course is a must-read!

创建者 Lipin A

Aug 05, 2019

Thank you very much. It was not easy, but very interesting to learn, to create and to code.

This course, especially its practice part got me deeper understanding what else I should to learn and read about.

Thank you! Good luck!

创建者 Anirban M

May 23, 2020

Teaching was good but since the title refers ML with python expected more deep dive with some ML associated libraries in python and implementation. The course was more over Theoratical but good for the beginners.

Thanks alot

创建者 Joe A

Feb 10, 2020

I enjoy this course - the content, the pace and the Notebook exercizes. It didn't bog me down and gave me a great insight into what Supervised and Unsupervised ML entails. I have lots to learn and practice ahead. Thank you.

创建者 Arnold K

Apr 07, 2020

this is an intermediate level but it blends in well with beginner's basics, allowing even people with less experience or perhaps only theory to jump in right away. Also makes foundation for advanced level. i recommend it.

创建者 Nhan T N

Mar 22, 2019

Amazing course. I learnt a variety of machine learning model here. Complete the course, I feel confident in understanding and applying them. It is also the foundation for me in further learning of machine learning. Thanks!

创建者 Venkata S M I

Nov 02, 2019

The course content provides a great insight into how we can create different types of models using Machine Learning algorithms. This is the best place to start if you want to really pursue a career towards Data Science.

创建者 Prakher N

Apr 15, 2020

The course is really good and comprehensive. You need to have some prerequisites of data visualization but the best aspect of the course is the instructor who teaches everything very smoothly and clears all your doubt

创建者 Nabham G

May 06, 2020

Crisp and clear course. Professors, up to the point and very clear explanation. The provided notebooks were super helpful for the final assignment submission. Everything was just awesome and organized well in detail.

创建者 Amitayu B

Mar 11, 2020

A wonderful course for beginners. Linear Regression, Classification (K-NN, DT, SVM, logistic regression) and Clustering algorithms (K-means, Hierarchical, DBSCAN) with its respective Python codings clearly explained.