Login using Social Account
Login using your credentials
What is closest to the mean value of the temp column after standard scaling?
3.497212e-16
-4.195150e16
4.035529e15
Taking you to the next exercise in seconds...
Stay here Next Exercise
Want to create exercises like this yourself? Click here.
No hints are availble for this assesment
Answer is not availble for this assesment
Go Back to the Course
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
Loading comments...