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.
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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
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Who This Book Is For
Intermediate to expert level professionals in the fields of data
science, data engineering, machine learning, and data management
