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In this spark project, we will continue building the data warehouse from the previous project Yelp Data Processing Using Spark And Hive Part 1 and will do further data processing to develop diverse data products.
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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 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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Get Started with Object Tracking using OpenCV and Python - Learn to implement Multiple Instance Learning Tracker (MIL) algorithm, Generic Object Tracking Using Regression Networks Tracker (GOTURN) algorithm, Kernelized Correlation Filters Tracker (KCF) algorithm, Tracking, Learning, Detection Tracker (TLD) algorithm for single and multiple object tracking from various video clips.
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MLOps using Kubeflow on GCP - Build and deploy a deep learning model on Google Cloud Platform using Kubeflow pipelines in Python
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Deep Learning for Time Series Forecasting in Python -A Hands-On Approach to Build Deep Learning Models (MLP, CNN, LSTM, and a Hybrid Model CNN-LSTM) on Time Series Data.
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