Understand the industrialization of machine learning (ML) and take
the first steps toward identifying and generating the
transformational disruptors of artificial intelligence (AI). You
will learn to apply ML to data lakes in various industries,
supplying data professionals with the advanced skills required to
handle the future of data engineering and data science. Data lakes
currently generated by worldwide industrialized business activities
are projected to reach 35 zettabytes (ZB) as the Fourth Industrial
Revolution produces an exponential increase of volume, velocity,
variety, variability, veracity, visualization, and value.
Industrialization of ML evolves from AI and studying pattern
recognition against the increasingly unstructured resource stored
in data lakes. Industrial Machine Learning supplies advanced, yet
practical examples in different industries, including finance,
public safety, health care, transportation, manufactory, supply
chain, 3D printing, education, research, and data science. The book
covers: supervised learning, unsupervised learning, reinforcement
learning, evolutionary computing principles, soft robotics
disruptors, and hard robotics disruptors. What You Will Learn
Generate and identify transformational disruptors of artificial
intelligence (AI) Understand the field of machine learning (ML) and
apply it to handle big data and process the data lakes in your
environment Hone the skills required to handle the future of data
engineering and data science Who This Book Is For Intermediate to
expert level professionals in the fields of data science, data
engineering, machine learning, and data management
General
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