Review my article

Hello everyone! I hope you are doing well.

I drafted an article for my LinkedIn titled “Machine Learning Guide for Petroleum Professional (part 1)”. This is some 3000 words, containing images, tables, and covering the very basics of ML and its mathematics. My audience is Petroleum engineers who don’t have knowledge of AI/ML. They are domain experts (having knowledge of Petroleum engineering). Before publishing it, I would love to get your feedback to improve it.

If your time allows you to review it, kindly let me know; I will send you directly. If not, no worries. Either way, have a wonderful day.


Hi @saifkhanengr ,

I can put some time in reading your article. I hope I can provide some valuable feedback.


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Thank you, Juan sir, for agreeing to review my article. I sent it to you.

Hi @saifkhanengr,

I can read it tomorrow. Would that be fine with your plan? If so, please also send it to me.


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Thank you, Raymond, for agreeing to review my article. I sent it to you.

Hello @saifkhanengr you can also send it to me, I might learn something new :wink:

Thank you, Isaak, for agreeing to review my article. I sent it to you.

Thanks, I will give you my review tomorrow

Hello @saifkhanengr,

So you have set up a simple regression problem, walked through the gradient descent, provided illustrations like tables, charts and graphs, and a link to python code at the end. I think it is a good approach! I will send you my comments on some of the content.

I am also aware of the list of goals in the last page, and that there will be a part 2. IMHO, I am just wondering whether you want to reserve Classification and Unsupervised learning for some later chapters of your tutorial series, because it seems we are focusing on Regression in this chapter, and I am sure interested audience will benefit more from chapters specialized on those two topics. :slight_smile:

Also, if you have a large group of audience for your tutorial, you might meet a few of them and try to go through it with them and ask for their feedbacks?



In part 2, I am planning to discuss activation functions (Relu, leaky relu, tanh, sigmoid) and mathematics of neural network (deep learning). In part 3, I will discuss real petroleum problem using NN (regression problem). In part 4, I am thinking of discussing CNN or classification but not sure. What do you suggest?

Regarding unsupervised learning, I don’t have any plan for it now as I haven’t used it yet with the petroleum problems. But in the future, maybe I do.

Yes, I sent that article to a petroleum professional who is familiar with AI/ML and using it with real-life petroleum problems.

Hi @saifkhanengr

I will be very happy to read it.

Muhammad John Abbas

Thank you @Muhammad_John_Abbas. But I already published it.

Maybe considering to incorporate the idea about non linear activation with your a simplified version of your part 3? Because to non technical folks, a good way to keep their attention is showing applications. If you allocate a full chapter only on a component (even though it is a critical one) and discuss their differences, it might be less interesting. You might compare the effect with/without a non linear activation?


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Thanks, Raymond, for such a good idea. I love it.

Actually, the Society of Petroleum Engineers (SPE) agreed to publish my articles in its magazine called JPT (Journal of Petroleum Technology). They asked me for a rough outline of all the parts, and I already sent them that, yesterday.
Part 1: Mathematics of ML
Part 2: Activation Functions
Part 3: Mathematics of DL
Part 4: A real case study.

Part 1 is already published and part 2 is almost complete.