Industry Use Case

Fetal Health Classification Using Advanced Supervised ML

This course focuses on the application of machine learning algorithms in determining the fetal health status based on different medical factors.

Application of Advanced supervised ML techniques for fetal health classification
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    Difficulty: Advanced

    Designed for those with a technical background or industry experience

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    Duration: Approximately 3 hours

Course Overview

  • Fetus is referred to the unborn baby that develops and grows inside the mother’s womb.
  • Pregnancy is a highly sensitive period both for the mother and fetus, as there can be multiple factors constantly influencing their health. Many times, there can be complications in the fetus which requires immediate medical attention and even a minor delay can cause mortality.
  • So a proper, dedicated analysis of fetal health to identify fetuses which are at the risk category is a crucial task for medical professionals. Hence, machine learning models can play a major role in classifying fetal health based on different medical factors.
  • Learn to apply classification algorithms to analyze fetal health based on different attributes and classify the fetal health status depending on the risk level.

What’s included

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Lifetime Access

Access this case study for life once completed

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Flexible Scheduling

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Desktop Only

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Skills you will learn

Model Building

Model Evaluation

Hyperparameter Tuning

Data Mining

Data Visualization

Machine Learning Concepts

ML Model Evaluation and Selection

Associated Learning Tracks

How it Works

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