Learn how to use Spark machine learning and data science to predict diabetes.
An early diabetes diagnosis can result in better management of the condition. The early diagnosis of the disease is frequently accomplished using data mining techniques. The relationship between the various attributes is also described in this research paper, which uses significant attributes to predict diabetes. The School of Disruptive Innovation, a company that develops innovative learning solutions for the digital age, created the Data Science: Hands-on Diabetes Prediction with Pyspark MLlib certification course, which is made available by Udemy.
Data Science: Hands-on Diabetes Prediction with Pyspark MLlib online course is an hour-long program that teaches students all the methods and ideas necessary to create, train, experiment, and assess machine learning models capable of identifying diabetes using logistic regression. Data Science: Hands-on Diabetes Prediction with Pyspark MLlib online classes include a variety of carefully crafted and designed tasks centered around data cleaning, diabetes datasets, logistic regression, performance evaluation, and Spark MLlib.
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Udemy
After completing the Data Science: Hands-on Diabetes Prediction with Pyspark MLlib online certification, students will be introduced to the principles of data science and functionalities of Spark MLlib (Spark machine learning) for predicting diabetes. In this data science certification, students will explore the methodologies involved with data cleaning, performance evaluation, and data processing as well as will acquire knowledge of the functionalities of Dataframes in PySpark. In this data science course, students will also learn about logistic regression models and will acquire the skills to process data using machine learning models using Spark MLlib.
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