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Working in a hands-on learning environment, led by our Machine Learning expert instructor, students will learn about and explore:
Load and understand a tabular dataset. As a data scientist, you should be comfortable working with tabular data.Query the dataset for deriving interesting reports.Clean the dataset accordingly so that it is well-suited for a machine learning model.Build and train machine learning models, like Logistic Regression and Neural Networks.Perform hyperparameter tuning techniques, like random search.Provide a summary of the performance of the machine learning models.

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Unlimited Duration

Last Updated

July 29, 2021

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In this course, you will be filling in the role of a data scientist employed by an organization’s cybersecurity manager. Lately, the employees of the organization are receiving a lot of emails containing links to phishing websites. Your task will be to develop a machine learning model for predicting whether or not an email that contains a link to a website is a phishing website or not. Phishing attacks are considered to be one of the most common types of online security threats, and are capable of breaking into an organization’s online security so as to extract confidential information like user passwords, financial information, and so on. The Internet Crime Report 2018 presents the effects of phishing websites.

Course Curriculum

    • Knowing the Dataset 00:00:00
    • A Quick Tour of Pandas 00:00:00
    • Submit Your Work 00:00:00
    • Getting Useful Information from the Dataset 00:00:00
    • Submit Your Work 00:00:00
    • Cleaning the Class Labels and Inspecting for Missing Values 00:00:00
    • Submit Your Work 00:00:00
    • Training a Logistic Regression Model 00:00:00
    • A Quick Primer on Logistic Regression 00:00:00
    • A Brief Take on Scikit-Learn 00:00:00
    • A Continuous Approach to Splitting Points: Logistic Regression 00:00:00
    • Submit Your Work 00:00:00

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