January 2020
Beginner to intermediate
432 pages
11h 24m
English
Content preview from Python for Finance Cookbook
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How to do it...
Execute the following steps to fit a neural network to a tabular dataset using fastai.
- Import the libraries:
from fastai import *from fastai.tabular import *import pandas as pdfrom chapter_10_utils import performance_evaluation_report
- Load the dataset from a CSV file:
df = pd.read_csv('credit_card_default.csv', index_col=0, na_values='')
- Identify the dependent variable (target) and numerical/categorical features:
DER_VAR = 'default_payment_next_month'num_features = list(df.select_dtypes('number').columns)num_features.remove(DEP_VAR)cat_features = list(df.select_dtypes('object').columns)preprocessing = [FillMissing, Categorify, Normalize]
- Create TabularDataBunch from the DataFrame:
data = (TabularList.from_df(df, ...
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