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In this hive project, you will design a data warehouse for e-commerce application to perform Hive analytics on Sales and Customer Demographics data using big data tools such as Sqoop, Spark, and HDFS.
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This big data project focuses on solving the small file problem to optimize data processing efficiency by leveraging Apache Hadoop and Spark within AWS EMR by implementing and demonstrating effective techniques for handling large numbers of small files.
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In this Azure Databricks Project, you will learn to use Azure Databricks, Event Hubs, and Snowflake to process and analyze real-time data, specifically in monitoring IoT devices.
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The goal of the BigMart Sales Prediction ML project is to build and evaluate different predictive models and determine the sales of each product at a store.
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Machine Learning Project in R- Predict the customer churn of telecom sector and find out the key drivers that lead to churn. Learn how the logistic regression model using R can be used to identify the customer churn in telecom dataset.
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Learn to implement various ensemble techniques to predict license status for a given business.
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