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What is the mean of the hum column?
hum
Hint: Use bikesData.describe() function.
bikesData.describe()
0.627229
0.190098
153.78689
189.463088
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1 Chapter Overview - Bike Rental Forecasting Project
2 End to End Project - Bikes Assessment - Basic - Description
3 End to End Project - Bikes Assessment - Basic - Importing the libraries
4 End to End Project - Bikes Assessment - MCQs - Which of the above libraries can be used to scale...
5 End to End Project - Bikes Assessment - Basic - Loading the data
6 End to End Project - Bikes Assessment - Basic - MCQs - What is the data type of dteday column of bikesData ?...
7 End to End Project - Bikes Assessment - MCQs - Which of these is a categorical feature?...
8 End to End Project - Bikes Assessment - MCQs - Do we need to hotcode the weathersit feature?...
9 End to End Project - Bikes Assessment - MCQs - Do we need an Imputer function to fill in the...
10 End to End Project - Bikes Assessment - MCQs - How many columns are present in the raw dataset?...
11 End to End Project - Bikes Assessment - MCQs - Which of these libraries can be used to standardize the...
12 End to End Project - Bikes Assessment - Basic - MCQs - How many unique values are there in 'yr' column of bikesData ?...
13 End to End Project - Bikes Assessment - MCQs - What is the mean of the hum column?...
14 End to End Project - Bikes Assessment - Basic - Cleaning the data - Dropping unwanted features
15 End to End Project - Bikes Assessment - Basic - Divide into training/ test dataset
16 End to End Project - Bikes Assessment - Basic - Defining some utility functions
17 End to End Project - Bikes Assessment - Basic - Cleaning the data - Feature Scaling
18 End to End Project - Bikes Assessment - MCQs - What is the mean value of the temp column after...
19 End to End Project - Bikes Assessment - Basic - Train and Analyze the Models - Preparing to Train the Models
20 End to End Project - Bikes Assessment - Basic - Train and Analyze the Models - Train DecisionTree Model
21 End to End Project - Bikes Assessment - Basic - Train and Analyze the Models - Train Linear Regression Model
22 End to End Project - Bikes Assessment - Basic - Train and Analyze the Models - Train Random Forest Model
23 End to End Project - Bikes Assessment - Basic - MCQs - Which of these models you will select based on mean RMSE?...
24 End to End Project - Bikes Assessment - Basic - Fine-Tuning the Selected Model - Choosing set of hyperparameter combinations for Grid Search
25 End to End Project - Bikes Assessment - Basic - Fine-Tuning the Selected Model - Defining GridSearchCV
26 End to End Project - Bikes Assessment - Basic - Fine-Tuning the Selected Model - Run GridSearchCV
27 End to End Project - Bikes Assessment - Basic - Fine-Tuning the Selected Model - Knowing Feature Importances
28 End to End Project - Bikes Assessment - Basic - MCQs - What is the n_estimators suggested?...
29 End to End Project - Bikes Assessment - Basic - MCQs - What is the max_features suggested?...
30 End to End Project - Bikes Assessment - Basic - MCQs - What is the max_depth suggested?...
31 End to End Project - Bikes Assessment - Basic - Evaluate the model on test - Preparing to test the final model on Test dataset
32 End to End Project - Bikes Assessment - Basic - Evaluate the model on test - Make Predictions on the Test dataset using Final Model
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