python quantile regression by using Deep neural networks packages but no hidden layers
Budget: $10 – $30 USD
do it for all main Deep NN packages
keras
tensor flow
fast.ai
pytorch
then it should be 4 solutions, all of them should provide good performance
data is mixture of categorical and continues features
at least 5 categorical features
at least 5 continues features
at least 100000 rows
data you find : several datasets ( more than 2)
see
primitive linear (or log-linear) model W \cdot \mathbf{x} + \mathbf{b} (where W is a weight matrix, \mathbf{x} = (x_1, x_2) is an input vector, and \mathbf{b} is a bias vector) without hidden layers,
https://tsmatz.wordpress.com/2017/09/13/overfitting-for-regression-and-deep-learning/
better to find and use existing code from web
keras
tensor flow
fast.ai
pytorch
then it should be 4 solutions, all of them should provide good performance
data is mixture of categorical and continues features
at least 5 categorical features
at least 5 continues features
at least 100000 rows
data you find : several datasets ( more than 2)
see
primitive linear (or log-linear) model W \cdot \mathbf{x} + \mathbf{b} (where W is a weight matrix, \mathbf{x} = (x_1, x_2) is an input vector, and \mathbf{b} is a bias vector) without hidden layers,
https://tsmatz.wordpress.com/2017/09/13/overfitting-for-regression-and-deep-learning/
better to find and use existing code from web