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Have you ever ever puzzled how automotive dealerships predict buyer spending? On this submit, we’ll stroll by constructing a easy neural community utilizing TensorFlow/Keras to foretell automotive buy quantities based mostly on buyer demographics and monetary information.
We’ll use the Car Purchasing dataset from Kaggle and break down each step of the method.
- Loading & cleansing the information
- Visualizing the dataset
- Preprocessing & scaling
- Constructing a neural community mannequin
- Coaching and evaluating the mannequin
- Making predictions
First, let’s import all of the Python libraries we’ll want for this venture:
import pandas as py
from pandas import DataFrame
import matplotlib.pyplot as plt
import seaborn as sns
from sklearn.preprocessing import MinMaxScaler
from sklearn.model_selection import train_test_split
import tensorflow.keras
from keras.fashions import Sequential
from keras.layers import Dense, Enter
import numpy as np
