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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 Python and MongoDB Project for Beginners, you will learn how to use Apache Sedona and perform advanced analysis on the Transportation dataset.
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The goal of this Spark project is to analyze business reviews from Yelp dataset and ingest the final output of data processing in Elastic Search.Also, use the visualisation tool in the ELK stack to visualize various kinds of ad-hoc reports from the data.
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In this machine learning project you will work on creating a robust prediction model of Rossmann's daily sales using store, promotion, and competitor data.
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In this LSTM Project , you will build develop a sentiment detection model using many-to-one LSTMs for accurate prediction of sentiment labels in airline text reviews. Additionally, we will also train many-to-one LSTMs on 'Alice's Adventures in Wonderland' to generate contextually relevant text.
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In this Deep Learning Project, you will learn how to optimally tune the hyperparameters (learning rate, epochs, dropout, early stopping) of a neural network model in PyTorch to improve model performance.
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