Sep 09, 2017
This course is ideally designed for understanding, which tools you can use to do machine learning tasks in python. However, for deep understanding ML algorithms you should take more math based courses
Oct 14, 2017
Very well structured course, and very interesting too! Has made me want to pursue a career in machine learning. I originally just wanted to learn to program, without true goal, now I have one thanks!!
автор: Siddharth S•
Jun 11, 2018
It would have been wonderful if the notebook codes were written and explained in the video the same way as in earlier courses in specialisation taking care of the implementation details as well.However still a Good Course of the Specialisation.
автор: Varada G•
Jul 23, 2017
It is a bit dense - be prepared to spend more time working through examples - and reading the reference book. The lectures, unlike the previous ones in this set, does not allow time for you to practice with the examples in jupyter notebook.
автор: Sparsh B•
Jun 08, 2020
This course was really helpful in understanding the working of various machine learning algorithms.
I was able to gain understanding of various evaluation techniques and there usage in different scenarios.
Thank you for this wonderful course
автор: Mark S•
Sep 01, 2020
Lots of useful information, but sometimes the content could have been better explained. Too many errata than necessary in the assignments at the end of each week. I found that the Jupyter notebook would stop working after about an hour.
автор: Xuening H•
Jan 29, 2020
Pro: I really like all the homework. The data is dirty and the work is a little bit challenging but doable.
Con: I prefer more animation in slices during the lectore to keep me concentrated. I get distracted watching the lecture's face.
Dec 18, 2019
I learned a lot about machine learning with python and would definitely recommend for someone with decent python background.. Some of the assignments have some very unnecessary technical hurdles that are unrelated to the material.
автор: Vinicius G•
Nov 20, 2017
Very hard but worth it. I only took one start off because I did not like the professor. Very sleepy voice and not very exciting explanations. Material was excellent and very helpful for the completion of assignments and quizzes.
автор: Shivam T•
May 02, 2020
I completed this course in specialization and this is the only course which is worth of your time, rest two before this course were your head against a wall.
Excellent course with all the understanding a student need.
автор: Nicolás S C•
Jul 28, 2018
Really good and applied course. It teaches you a lot of powerful tools for machine learning.
The only negative thing is that the week 4 cover hard topics, and the explanations are vagues sometimes, but nothing too terrible.
автор: Caspar S•
May 01, 2020
Very happy with the course content.
On the other hand, certain instances need to be updated/corrected.
For several assignments, the files don't load and you need to dig through the forums.
It would've been 5 stars otherwise.
автор: Gourav S•
Dec 28, 2019
It can be more detailed. It is on broader terms only. I will recommend Andrew Ng ML course to do as well because it covers too many things than this module. Otherwise, this is a good module as well. :) Enjoyed doing it.
автор: Qitang S•
Mar 06, 2019
Good Introduction Courses, but need more guidance for assignments as there is a gap between two of them. Assignments do need some more hours to finish. In all, a great course for anyone to break into machine learning.
автор: Cat-Tuong N•
Oct 03, 2020
Challenging and fun course. The number of topics is on the high side. Maybe break this into 2 courses? The programming assignments are fun. You will need to go to discussion forum to solve often encountered problems.
Jul 31, 2017
Much better than the second course, the materials are carefully prepared and organized, teaching staff are very helpful in solving issues, however, assignments are not so challenging, still needs improvement.
автор: J W•
Jan 29, 2018
Comprehensive and interesting course in Machine Learning. The use of Scikit Learn helps to give a concrete understanding of ML as well as how many specific algorithms can be utilized in real world problems.
автор: Vishal S•
Jun 23, 2018
It's a nice course. It'll familiarize you with different models, evaluation metrics and basics of machine learning and let you practice with some of the real world datasets during assignment.
автор: Muzahidul A•
Jul 07, 2020
assignments were so good. I think there was not enough information given for the quiz tests. And also the code given was not properly explained. But the materials were so good for practice
автор: Raul M•
Apr 28, 2018
A good introduction to algorithms available in python. I didn't give it a five stars because I 'm still confused on which algorithms to pick/use when I want to work on real data problem.
автор: Julien Z•
May 06, 2020
Very good mix of video and python notebook. Some improvement can be done with the AutoGrader like get back the error python stack trace.
Globally, very good course - strongly recommanded
автор: kai k•
Jun 04, 2018
The final assignment passing was a little too east,
there not being need to use fully what I learnt.
Still,the overall course was very good, and I am willing to keep on take other courses.
автор: Vinicius d A O•
Mar 16, 2020
This course was very good, with a lot of information and important tips for me. The instructor is good but he is long winded, so this course was very long with videos during 20 minutes.
автор: Saman H A•
Aug 15, 2019
- more technical materials, comparisons and better classified details should've been provided, especially to be more proportional to the assignments.
-again, subtitles were full of typos
автор: philippe p•
Jun 07, 2017
The course is well balanced but the progression becomes quite agressive at Week3 and culminate at Week4 with a real life case assignment without much guidance. Great experience dough.
автор: Vaishnavi M•
Jun 29, 2020
Amazingly explained. An intermediate Machine Learner would definitely get clarity of concepts already learned and also new concepts explained so skillfully with graphs and diagrams.
автор: Alex E•
Aug 27, 2018
Good overview of methods in ML. Would have been nice if the lectures contained a little more mathematical rigor and explanation of why and how the various algorithms are effective.