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Dataset I - Bike rentals

  • Using sklearn and XGboost Linear Regression
  • Decision tree regressor
  • Random forest regressor
  • AdaBoost regressor
  • Gradient boosting

Source: UCI Machine Learning Repository Dataset

import jovian
jovian.commit(project='dataset1-lr', filename='dataset1-lr.ipynb')
[jovian] Update Available: 0.2.28 --> 0.2.32 [jovian] Run `!pip install jovian --upgrade` to upgrade
[jovian] Attempting to save notebook.. [jovian] Updating notebook "patxigad/dataset1-lr" on https://jovian.ai/ [jovian] Uploading notebook.. [jovian] Capturing environment.. [jovian] Committed successfully! https://jovian.ai/patxigad/dataset1-lr

Getting the data

# main imports
import pandas as pd
import datetime as dt
import numpy as np

import seaborn as sns
import matplotlib
import matplotlib.pyplot as plt
%matplotlib inline

matplotlib.rcParams['font.size'] = 14
matplotlib.rcParams['figure.figsize'] = (9, 5)
matplotlib.rcParams['figure.facecolor'] = '#00000000'

# silence warnings
import warnings
# upload 'bike_rentals' to DF and display first few rows
df = pd.read_csv('https://media.githubusercontent.com/media/PacktPublishing/'