Question

if someone has a dataset and they want to build a neural network, how would someone be able to progam that in python for a machine learning project

Answer 1

Python is probably the best option for a machine learning project. Now, first of all check what kind of dataset you have, by what kind i mean is that if its an image dataset or text dataset or a numeric dataset with rows and columns of values. Now the steps for creating a neural network in python are:

1 Decide which neural network you want to use. If its an image dataset then CNN is best( ANN would also work), if its and text based dataset RNN is usually used and if a numeric dataset then ANN is suitable.

2 Now, there are various machine learning librabries like scikit, scipy, tenserflow, keras etc with the help of which you can easily build your neural network.

3 The libraries like numpy and pandas are very essential for reading and storing your data from your dataset as arrays for training purposes of the neural network.

4 First you read your dataset using pandas or something like pandas. Then based on the dimentions and type of your data start building your network using the libraries. You need input, hidden and output layers in your network. Use activation functions like sigmoid, relu, etc according to your requirements. After that use some kind of gradient descent algo like SGD or ADAM for calculating loss and updating weights of your network.

5 Once you build yor network you can start training. Best part about it is that if you dont get desired results you can change parameters in the network to increase accuracy.

NOTE: Tensorflow and keras are frameworks built on python so the syntax is bit different. And you can also build an entire neural network from scratch in python just using numpy library.