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Udemy - Cluster Analysis And Unsupervised Machine Learning In Python (Updated 2-2020)
TORRENT SUMMARY
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Data science techniques for pattern recognition, data mining, k-means clustering, and hierarchical clustering, and KDE.
What you'll learn
Learn Apache Beam with its Real-Time implementation.
Build Real-Time business's Big data processing pipelines using Apache Beam.
Learn a portable programming model whose pipelines can be deployed on Spark, Flink, GCP (Google Cloud Dataflow) etc.
Understand the working of each and every component of Apache Beam with HANDS-ON Practicals.
Develop pipelines for Real world Big data case studies in various business domains.
Data-sets and Beam codes used in lectures are available in resources tab. This will save your typing efforts.
Course will be updated upon each new Beam version update.
Requirements
Know how to code in Python and Numpy
Install Numpy and Scipy
Matrix arithmetic, probability
Description
Cluster analysis is a staple of unsupervised machine learning and data science.
It is very useful for data mining and big data because it automatically finds patterns in the data, without the need for labels, unlike supervised machine learning.
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