A Gentle Introduction to Deep Learning

PyCon 2017 talk

This Jupyter notebook only contains code for the talk.

Part 1: Implementing linear regression using numpy

The problem: predicting house prices.

We have three pieces of information about each house, which we call the features:

We'll represent these in an array we'll call x.

And we have the target value we're trying to predict, the house price, which we'll call y.



In [1]:

    
import numpy as np



In [2]:

    
# x is the features we're using as information to predict...
x = np.array([1250, 350, 3])

# ...y, the target value
y = 345000