Deploy Machine Learning & NLP Models with Dockers (DevOps) (Udemy.com)

Awesome course! To the point and for advanced user who wants to go the the next level. I would expect more examples as suggested by the instructor to try reading and writing on sql, or file etc - which will greatly enhance the course even further.

Videos are excellent understanding but having doubts which are not being cleared. If any help on the doubts it will be really helpful

Having some docker-specific error debugging in the lectures was a nice touch, but all the Python spelling errors wasted a lot of unnecessary time that could have been prevented with a little extra preparation

Concepts are presented in very clear and professional . I am really enjoying this course

This course fulfills exactly what it propose. Learned about flask framework, build machine learning using docker, build a WSGI, clustering & NLP processes to deploy. Great classes!

1/ Does not cover some dependencies such as usage of pip, at least in the order that you need them.2/ Explaination of GET and POST verbs is misleading.3/ Explaining why we want to perform an action with another question, such as "Why not build the classifier?", is not very informative.4/ Using colloquialism's such as "live life king size" and "bad boy" is not very informative.5/ Using "paint" instead of a prepared images seems poor.6/ The presenter is unprepared generally for the material that he is presenting.7/ Misses important parts related to the subject such as retraining models and how this is done.8/ Spends lots of time talking about the ML implementation, rather than the subject matter of deploying such models.Summary: Competitors do a much better job.

I have been wanting to learn this stuff for a long time, but never knew where to find it. I am so excited to try this out on my own projects! The instructor explains it so simply. Edit: This instructor does not appear to be responsive to questions in the Q&A section.

A very quick crash course that covers only the necessary topics in minimum possible time. The ML part is bare minimum. So, if you're thinking of learning ML part through this course, don't keep much expectations. As far as docker part is there, the instructor teaches the basics and develops a basic application, rest ML applications in course are left to dockerize ourselves as exercise.

The author explains very good and the course delivers all that is in the content. I was able to learn docker, although I had to pass through a lot of debugging to do the first homework. I learned a lot! Negative points: 1-the english legends have a lot of mistakes 2-there are forum questions that have not been answered.

The course is well explained. However, there are few bugs and the instructor does not answer questions.

I love the pace and the way this instructor explained the programming syntax, problem and resolution. My only challenge is he should have expanded the Editor all the way to the right and move the terminal console below or above it. That way, students can see all the codes that was written. I know that I can download the code from the resource file, but watching and seeing everything in one place is a trivial bonus. Other than that, I love the practicality of this course.

Vivek has elaborated the difference between Docker containers and VMs really well.