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noc19-cs33 Lec 27 Decision Trees for Big Data...
Introduction This tutorial provides a comprehensive guide to understanding and implementing decision trees withi...
noc19-cs33 Lec 26 Parallel K-means using Map R...
Introduction This tutorial provides a comprehensive guide to performing parallel K-means clustering using MapRed...
noc19-cs33 Lec 25 Machine Learning Algorithm ...
Introduction This tutorial will guide you through the implementation of the K-means machine learning algorithm u...
noc19-cs33 Lec 24 Big Data Machine Learning (Part-II)
Introduction This tutorial provides a comprehensive overview of key concepts and techniques discussed in the vid...
noc19-cs33 Lec 23 Big Data Machine Learning (Part-I)
Introduction This tutorial provides a comprehensive guide based on the lecture "Big Data Machine Learning (Part-...
noc19-cs33 Lec 22 Introduction to Kafka
Introduction This tutorial provides a comprehensive overview of Apache Kafka, as introduced in the lecture from ...
noc19-cs33 Lec 21 Sliding Window Analytics
Introduction This tutorial covers sliding window analytics, a key concept in data analysis that helps manage and...
noc19-cs33 Lec 20 Spark Streaming and Sliding W...
Introduction This tutorial provides a detailed overview of Spark Streaming and sliding window analytics based on...
noc19-cs33 Lec 19 Spark Streaming and Sliding ...
Introduction This tutorial provides a detailed guide on Spark Streaming and Sliding Window Analytics, based on i...
noc19-cs33 Lec 18 Design of HBase
Introduction This tutorial covers the design principles and architecture of HBase, a distributed, scalable, NoSQ...
noc19-cs33 Lec 17 CQL (Cassandra Query Language)
Introduction This tutorial provides a comprehensive overview of CQL (Cassandra Query Language) as discussed in L...
noc19-cs33 Lec 16 Design of Zookeeper
Introduction This tutorial covers the design principles of Zookeeper as discussed in the lecture from IIT Kanpur...