About the Dataset and Task:
Any business wants to maximize the number of customers. To achieve this goal, it is important not only to try to attract new ones, but also to retain existing ones. Retaining a client will cost the company less than attracting a new one. In addition, a new client may be weakly interested in business services and it will be difficult to work with him, while old clients already have the necessary data on interaction with the service.
Accordingly, predicting the churn, we can react in time and try to keep the…
Dataset Used: https://www.kaggle.com/mirichoi0218/insurance
My Notebook: https://www.kaggle.com/tanishsawant2002/regression-85-score
Description Of The Dataset: (An excerpt from Kaggle)
Machine Learning with R by Brett Lantz is a book that provides an introduction to machine learning using R. As far as I can tell, Packt Publishing does not make its datasets available online unless you buy the book and create a user account which can be a problem if you are checking the book out from the library or borrowing the book from a friend. …
Notebook used for this lesson: Click here(upvote if you liked it😉)
A random forest is a meta estimator that fits a number of decision tree classifiers on various sub-samples of the dataset and uses averaging to improve the predictive accuracy and control over-fitting. The sub-sample size is controlled with the
bootstrap=True(default), otherwise the whole dataset is used to build each tree. ~sklearn docs
The above definition is very convoluted, let's break it down.
In machine learning, there’s a concept called decision trees. A tree can be “learned” by splitting the source set into subsets based on…
Jupyter notebooks are pretty much necessary to get going with data science using python or R.
Here is the way you can install it using PIP
Run following command in the command prompt.
pip install virtualenv
This will install a package called virtualenv, which can be used to create a virtual environment.
To make sure that virtualenv was installed successfully, run following command.
Good! Now let’s create a virtual environment.
It is as simple as that!!