AD
May 24, 2020
It is a great project and an excellent experience to learn practical exposure to Linear regression with nmpy and python. I am waiting to get another project.
VB
Jul 9, 2020
Best Project ever we have seen, all plotting and code are explain in very well manner and its definitely increase my knowledge in machine learning
By Lizardo R
•Mar 23, 2020
More programming background was necessary
By Ashish G
•Apr 23, 2020
because of cloud desktop, speed of videos was very slow
By Manav G
•Jun 17, 2020
The rhyme was very slow.....and in poor quality...video quality was intermediate but software quality is poor
By Mohit M
•Apr 27, 2020
Project is awesome but delivered in a boring way.
By Subikesh P S
•Jun 1, 2020
The teaching in the project was great! But I think if the dataset of the project was better in terms of number of features, it would have been better. For this to be a complete project, there should be a test data, and accuracy should be calculated, which was not done in this project. Overall the structure of this project is so easy and can be useful for those who really start up with ML.
By Purvansh P
•Jun 6, 2020
The important points should be discussed thoroughly, The instructor was not able to make the user understand why he was using this and that part, he lacked some teaching skills.
By SHUBH D
•Aug 29, 2020
Need to explain the basics first.
By Deepak S
•Jun 12, 2020
The purpose and logic are not explained well, also some ideas about library functions used should be described in bit, what they are doing, why are they used. Little approach about programming is also required to be added. I was pretty not satisfied with the course.
By Jatin K
•May 14, 2020
Not for beginners! Waste of time if you are entering into this field for the first time. The instructor just skips 80 % of the concepts and assumes you know everything.
Wasted my 2 hours for sure.
By Deleted A
•May 1, 2020
Server too slow.
By Kim D
•May 14, 2020
I am really happy with this course. I was needing to learn how to build a simple linear regression model using only Python and NumPy, and after finding countless articles and other tutorials that made little sense (I'm a complete noob) I finally found this one. I was skeptical because of my luck with the other resources I found, but this completely did the trick. Being able to code along with the video was so helpful, too. I'm so happy I finally found this tutorial that guided me step by step with clear explanations.
By Parag
•Feb 8, 2022
Simple and efficient. The instructor has clear diction and does not waste time with useless jargon.
You need some background idea of ML before doing this course. Otherwise, you may have difficulty understanding what is going on.
Would have appreciated a short 5-min video on numpy and other ibraries used here - so that it was clear why certain functions were called here.
By Rukshan M
•Jun 4, 2020
Understand how linear regression works behind the scenes! This project was very valuable for me because it helped me to turn my theoretical knowledge into practice. Enrol this project only if you're familiar with Python, NumPy, pandas, matplotlib, seaborn, matrix algebra, linear regression, gradient descent, Jupyter Notebook. Otherwise, you will not understand anything!
By Mun L K
•Jul 3, 2020
I have read many articles and enrolled in several courses attempting to teach linear regression from scratch. This course provides the best balance of sufficient math to enable a deeper understanding and the practicality of seeing a simple implementation of the algorithm actually working in numpy. Hope to see a similar project for neural networks.
By YOGESH P
•May 26, 2020
This project was just the right one to get me started on my path to machine learning. I am currently setting out to explore Machine Learning and was in a dire need of learning some basics. I would like to thank Coursera and the project instructor to guide me to learn some new and valuable skills.
By A V
•Jul 2, 2020
This refreshed my foundations of machine learning skills with absolutely simple libraries that are rather powerful when comes in predictions and the guide was really helpful throughout the course and beginners can get clear idea of what is happening with models.
By Shashank G
•Jul 26, 2020
Can definitely call this course an informative one as the instructor literally explained each and every line of the code. But it'd be much beneficial if the candidate gather a basic understanding of Linear regression before starting this course
By Ashish V
•Apr 9, 2022
Guided projects are just amazing while working around Hands-on side by side which gives quite Good Understanding.
one of the best way to explain and teach how the bloc of code executes and NoteBook helps us to execute chunks of code.
By Likith R
•May 18, 2020
It was helpful as recently I had seen a linear regression problem which was too complicated. But this project helped me understand the basics properly to continue my interest in Python language. It was interesting. Thank You
By Rahul S
•Jun 6, 2020
Good Course . I really wanted someone to guide me write the library functions from scratch to help me understand the core mathematical concept behind the linear regression. This course was what I wanted all along.
By Abhijit T
•Apr 9, 2020
This course covered all the concept taught in the machine learning course of Coursera. I am glad that Snehan Sir was so clear during his guide lecture that I was able to relate my concepts with the project work.
By Ankur D
•May 25, 2020
It is a great project and an excellent experience to learn practical exposure to Linear regression with nmpy and python. I am waiting to get another project.
By Vikas S B
•Jul 10, 2020
Best Project ever we have seen, all plotting and code are explain in very well manner and its definitely increase my knowledge in machine learning
By Dolly S
•Jan 7, 2023
This course has all of the software needed preloaded and it was easy to learn with having to open programs and libraries.
By Muhammad S
•Oct 7, 2020
Great experience especially for beginners to get hands-on practice to a deep understanding of fundamental concepts.