There was a course, but can't find it again, on python and learning machines?

Question

Python

Good afternoon. A few months ago I saw a course of articles either on neural networks, or on machine learning in python.
The meaning of the first lessons is that an online library is used, there is some kind of dataset or you upload your table, and you write code in python, and it builds graphs for you, predicts further behavior and other delights. The library is either from Google, or from someone else known. There was something about height, weight and typical values, and values ​​that are out of the normal typical.

Help find these articles..

Or maybe something else you would like to read. The task is this: There are several price lists of competitors with a similar service. The price of the service (printing) depends on several parameters (the larger the print run, the cheaper, the larger the image, the more expensive, the more colors, the more expensive). But the dependence can not be understood, I want to apply machine learning for this. Charts to look at, reflect on and give birth to your pricing.

Answer 1

That's why, a super-accurate description " either by neural networks, or by machine learning in python ...... an online library is used ...... there is some kind of dataset .... and it builds graphs for you , predicts further behavior and other delights ...... .either from Google, or from someone else well-known ... ..... Or maybe you can advise reading something else. ".
the network is not just a lot, but almost everything that is there.
Tired of rewriting for the lazy every time. The day before yesterday I already compiled for another suffering knowledge, there is literature and courses:
Literature or any math courses for machine learning?
And in terms of the task itself, the problem is that each of your competitors may have their own special model, sometimes fundamentally contradicting others. With the help of ML, you can either try to understand which competitors have similar models (clustering problem) or for each of the competitors (or their selected groups) create their pricing model. However, the meaning of the last action is more than doubtful.
And look at the graphs - this is generally not related to ML in any way.
In general, it's time to put things in order in your thoughts and move from "think" to "explore"