How to train a neural network?

Question

Neural networks

Hello everyone :) In the project, I faced the following task:
At the input I have 16 neurons, each of which has already been reduced to a number in the range from 0 to 1, at the output I should get a chance of 1 for these values.
For clarity, I assembled something like this to train the network:

• 0.1 | 0.2 | 0.4 | 0.4 | ... | one
  
• 0.3 | 0.1 | 0.8 | 0.3 | ... | one
  
• 0.7 | 0.8 | 0.2 | 0.1 | ... | 0
  ...
  

The first numbers are the values ​​of the neurons, the last is what I have at the output (0 or 1).

The task seemed trivial to me, so please advise some sources, methods, something, so as not to dig too deep into the world of machine learning and solve it in a short time.

Answer 1

16 inputs. binary output. Why is there a neural network?
Take any classic classifier - kNN, DecisionTree, Logistic regression, ... whatever you like, and go ahead. Naive Bayes will give an excellent membership probability. Fortunately, everything has already been implemented before us.
Implemented - in Python - scikit-learn, in R, in any more or less serious machine learning package.
The neural network - except that there is nothing to do, a great desire to delve into the topic and a lot of free time. They have their own scope. Do not poke a neural network into any hole. The microscope is not intended for hammering nails.