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How To Quickly Develop A Machine Learning Model With Data robot?

One Of The Points That You Should Pay Attention To As A Machine Learning Expert Or Data Scientist Is To Make The Process Of Building Models Smarter. 

Machine Learning Model With Data robot, the world of artificial intelligence is moving in a direction where cloud-based services create intelligent models based on the data you provide.

Accordingly, if you want to use such services, create services based on artificial intelligence, or have no experience building intelligent models, this article will provide you with basic and exciting information in this field.

What is DataRobot?

DataRobot is based on open-source algorithms and uses AI-ready services to provide available features for building and deploying machine learning.

DataRobot is an advanced commercial AI platform that democratizes data science and automates the end-to-end process of designing, implementing, and deploying intelligent algorithms. DataRobot supports the latest open-source algorithms and is cloud-centric, capable of being deployed through the cloud, as an on-premises service, or as a full developer-managed AI service. In all cases, users or companies can use the power of AI to achieve efficient business results. This article will teach us how to build a machine learning classifier model based on DataRobot.

We use data on a banking institution’s marketing campaign based on telephone calls about marketing activities. It is often contacted to determine whether a depositor or, more specifically, a bank customer would like to make a term deposit with the bank.

We will create a classification model to investigate whether we should contact customers or not. More precisely, artificial intelligence will suggest which customers to contact.

First, we start by uploading the data because the model cannot learn anything without data.

Upload data

The thing that you should pay attention to before using the above service is that there are special conditions for using data as follows:

If your data file is more significant than 200MB, you will need to create a job ID to use it, as DataRobot has limited direct uploads to 200MB.

Next, click on Data in the taskbar at the top of the web page to access the data. After loading the data, you must select the target column. DataRobot creates a counting chart for categories if the target column is discrete.

Model selection

Next, we are going to check the autopilot mode.

After selecting the above option, click on the start button to see a screen like the one below.

Calculate the results

Deploy the final model

last word

DataRobot can generate predictions one by one or in large batches by importing a file.

Any machine learning model can be turned into a potential AI application using DataRobot, allowing anyone in the ecosystem to interact with the original model’s predictive insights.

This utility will enable you to compare a forecast with historical results, examine the reasons for the estimates, and change input parameters to see how it affects those results. Overall, in the above article, we tried to show you the construction and deployment of a predictive model using DataRobot.

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