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Вернуться к Машинное обучение с использованием Python

Отзывы учащихся о курсе Машинное обучение с использованием Python от партнера IBM

4.7
звезд
Оценки: 9,910
Рецензии: 1,626

О курсе

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....

Лучшие рецензии

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.

FO

Oct 09, 2020

I'm extremely excited with what I have learnt so far. As a newbie in Machine Learning, the exposure gained will serve as the much needed foundation to delve into its application to real life problems.

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1201–1225 из 1,614 отзывов о курсе Машинное обучение с использованием Python

автор: C. L P

Sep 17, 2020

This was the meat of the IBM data science course set for me, and was really very informative. Extremely well presented and clear. I would have liked a bit more depth in this material, with a bit less emphasis on python/sql/tools issues.

автор: Ramakrishnaprasad

Dec 17, 2019

The Course is very valuable content for beginners and easy to understand, the explanation is very good with simple words and live examples. i had refereed this course to my friends to improve their technology stack, their feeds is also good.

автор: Olivia D

Jul 16, 2020

More interactive questions for the programming exercises. Also, the peer marking has room for error since we can't always identify mistakes in others code easily. A code that checks answers for each point and gives feedback would be better.

автор: S C

Feb 22, 2019

Good introductory course for people to start off with Python. This course touches upon various aspect of the coding language and the lab environment made it easy to practice things. Looking forward to such informative courses going forwards

автор: Stéphane D

Feb 01, 2020

4 stars = Great Course!

missing start = Cloud Management / course interrupted because of month credit expired, expected promo code never available...

Suggestion : Cloud "Assets" available for the entire course without a stupid limitation

автор: DINESH K K

Apr 07, 2020

All over about the course is good but little bit math behind the algorithm was not explained (iterative) and implementation with python also not discussed. Over all you will get to learn many things from this course.

Thanks

All d best

автор: Binod M

Jun 29, 2020

I was not satisfied with the way my final assignment was graded wrongly without any feedback. But overall the course is definitely helpful in introducing machine learning concepts with implementation using popular python libraries

автор: Phalin D

Jun 02, 2020

The content in the course is very detail and clear. They illustrate each time difference technique where we can use in machine learning. Though, I found the exercise in are a little bit easy, but it's help a lot with learning.

автор: Venkatesh K

Jun 03, 2020

Best course to understand basic working of all algorithms. Assesments are goof for fresher and looks easy if one knows already. Ensemble techniques should also be included in this such as RandomForest and Boosting Algorithms.

автор: GaviniSaisandeep

Aug 13, 2020

Great Course to get started with the practical Machine Learning, This course is for beginners who wants to get to know the Machine Learning Concepts and its implementation.

Great Step for the next courses like deep learning

автор: Sen Y

Jul 23, 2020

Very informative, I learnt a lot about model training and machine learning techniques. However I found some parts of the materials were jumping too fast to result i.e. not enough step to step explanation for the codes.

автор: Dominic M L C L

May 14, 2020

One of the better courses in the series. Lab sections can be better with more practice questions. Final project could have been more comprehensive as well instead of focusing on just one section in the entire course.

автор: Rahul C

Jun 18, 2020

A good course to start your AI journey with python and scikit learn. Four stars because code should be explained in a video, but it has an advantage that when you search something you always discover something new.

автор: Rohan B

Jul 25, 2019

This course provides excellent practical implemented datasets which gets you started but a person willing to do this course must have to learn various things on his own as well to completely understand this course.

автор: Tim d Z

Mar 12, 2020

Videos contain great content, are very clear and to the point. However, the malfunctioning Lab environments really took the speed (and fun) out of the course. Overall it was an interesting and valuable course.

автор: Ameer M S

Mar 24, 2019

if only financial aid was available for this course it would have been awesome, the content is pretty good, but the labs are pretty confusing as I haven't been able to figure how to register them as completed.

автор: Diego I

Mar 19, 2020

Es un curso muy completo que cubre muy bien los fundamentos básicos sobre machine Learning. Al final de este curso tendrás una noción de que algoritmos son útiles para cada una de las necesidades mas comunes.

автор: Luis H

Jun 24, 2019

Las explicaciones en los videos son bastante buenas, aunque las actividades no permiten comprender del todo lo que se debe realizar para el examen final, cuesta mucho trabajo desarrollar la última entrega.

автор: Surya P S

Jul 26, 2020

The course was very concise and very helpful for people who want to learn ML for a career. It would have been even better if there were some OPTIONAL readings so that we can also learn the theory part.

автор: Sri R

Jul 04, 2020

This course is suitable for beginners. One can get hand-on experience on creating machine learning model and basic working knowledge of some classical machine learning algorithms. Overall, good course.

автор: Sudipan B

May 24, 2020

A very good and informative one comes with online lab service. But the price for earning a certificate in this course is bit high that's why i'm giving it a 4 star. But the overall experience is 4.5/5.

автор: Shiva C P

Jul 26, 2020

Great course! One idea for improvement > Some of the comments in the Clustering and Recommender systems labs are hard to understand. Maybe you can rephrase / add more text to make it more intuitive.

автор: Cherif H W A

Jan 01, 2020

could be split in two courses to be given enough focus. it was very condensed and needed more time and explanation in each section. The instructor was very good but more details would have been nice

автор: Tural G

Sep 25, 2020

Excellent course for beginners to data science field. Would have been better if the final project also included flavor of other ML methods such as Regression, Clustering or Recommender Systems.

автор: CHEN X

Jun 25, 2020

This course walks us through the fundamentals of machine learning methods. The capstone project is very useful for those who have previous knowledge of machine learning and Python programming.