Practical Deep Learning with Tensorflow 2.x and Keras (Udemy.com)

Although the lecture is good, but the explanations are discussed too quick and few things are still left to understand. It is advisable to discuss some Algorithm first, before starting the code, which then can be applied to build the code and understand the logic behind. Just a suggestion !!

Up until module 17 the course had good explanations, was informative, and easy to follow and understand. Modules 17, 18, 20, and 23 are not explained in any details. It feels as a "code along" exercise with virtually non explanations. This portion of the course is rushed through for the sake of completion. As no knowledge of ML is required for this course, those modules need to be explained in more details, 5 minutes per module is definitely not enough.

This is definitely one of the best practical courses available on Udemy. This course perfectly combines enough theory and practice. And it is really great that high-level API such as Keras has been chosen (anyway it is adopted in TensorFlow2.0, so it is worth learning). Mohammad has a unique talent to explain complex things clear and illustrate them with the relevant code. I really hope for the following course on advanced topics =) Best regards, Ilia.

The first three modules are a waste of time IMHO. The course is about DL, so the people who watch it should be familiar with the basics of ML. I expected to see much more examples of NNs written in Keras. However, in general, the course is rather good and provides some useful examples, as well as several good key points regarding the model parameters in Keras.

If you have a bit of background in machine-learning, this is an excellente course to get you up and running in a few hours! The instructure is very pragmatist to in putting the content together and clearly has a solid scientific background. He is responsive in Q&A section to help you with your questions. A quick review of all posiible (default) architectures from Keras API is missing from the course.

I'm not a math wiz, never have been, won't ever be. But I've been a programmer for most of my career who likes to experiment with almost anything opensource so I went through a frustrating time trying to find a book or resource that would help me understand ML/DL without having to first understand the incredible math behind it all. So this course was perfect and kudos to Dr Nauman for thinking of people like me and creating this introduction to ML/DL. I've already viewed all videos at least 2 times (some maybe 5-6 times) and I'm going to have to view the videos and do the code-along several more times before I really understand this stuff. But this should get me ready to start experimenting with DL in real life applications. Thanks very much Dr Nauman

A lot of instructors have a habit of making huge jumps in difficulty or dance through a new concept without taking the time to fully explain it. What I like about Mohammad Nauman's course is that everything is paced so perfectly, and you wind up with several real practical examples that you can go back to. Whenever a new concept gets introduced, it's always with an explanation of what we're going to do, how we're going to do it, and then showing what happened. It fit my learning style perfectly.

Very easy to understand even if you have never used Keras. The case study was very informative and related to my interest. And the instructor is just awesome, the way he explains and make the thing easier. I am really excited after taking this course. The teaching approach shows his experience in content knowledge. I recommend this for all computer science personals.

Hello, This course really given boost to my skills with machine learning. I had very little knowledge of machine learning and now I am able to understand practical meaning of regression, classification and deep learning. The buzz word of deep learning has really created a hype and I think it is no longer a mystry after I took this course. Thanks to the author.

One of the best courses I've taken. The article by Dr. Nauman on free GPU access for experimentation was just what I needed right now. He seem extremely knowledgeable and covers just enough detail and everything is explained through code. I've tried to learn keras from different sources before but this is the best resource put together that made everything fit together perfectly.