Data Science and Big Data Analytics – EMC Education Services

Technological advances and the associated changes in practical daily life have produced a rapidly expanding “parallel universe” of new content, new data, and new information sources all around us. Regardless of how one defines it, the phenomenon of Big Data is ever more present, ever more pervasive, and ever more important. There is enormous value potential in Big Data: innovative insights, improved understanding of problems, and countless opportunities to predict—and even to shape—the future. Data Science is the principal means to discover and tap that potential. Data Science provides ways to deal with and benefit from Big Data: to see patterns, to discover relationships, and to make sense of stunningly varied images and information. Not everyone has studied statistical analysis at a deep level. People with advanced degrees in applied mathematics are not a commodity.

Relatively few organizations have committed resources to large collections of data gathered primarily for the purpose of exploratory analysis. And yet, while applying the practices of Data Science to Big Data is a valuable differentiating strategy at present, it will be a standard core competency in the not so distant future. How does an organization operationalize quickly to take advantage of this trend? We’ve created this book for that exact purpose. EMC Education Services has been listening to the industry and organizations, observing the multi-faceted transformation of the technology landscape, and doing direct research in order to create curriculum and content to help individuals and organizations transform themselves. For the domain of Data Science and Big Data Analytics, our educational strategy balances three things: people especially in the context of data science teams, processes such
as the analytic lifecycle approach presented in this book, and tools and technologies in this case with the emphasis on proven analytic tools. So let us help you capitalize on this new “parallel universe” that surrounds us. We invite you to learn about Data Science and Big Data Analytics through this book and hope it significantly accelerates your efforts in the transformational process.

Related posts:

The hundred-page Machine Learning Book - Andriy Burkov
Python Machine Learning Second Edition - Sebastian Raschka & Vahid Mirjalili
Artificial Intelligence with an introduction to Machine Learning second edition - Richar E. Neapolit...
Building Machine Learning Systems with Python - Willi Richert & Luis Pedro Coelho
Python Machine Learning Third Edition - Sebastian Raschka & Vahid Mirjalili
An introduction to neural networks - Kevin Gurney & University of Sheffield
Artificial Intelligence by example - Denis Rothman
Python for Programmers with introductory AI case studies - Paul Deitel & Harvey Deitel
Machine Learning - The art and science of alhorithms that make sense of data - Peter Flach
Medical Image Segmentation Using Artificial Neural Networks
Machine Learning - A Probabilistic Perspective - Kevin P.Murphy
Python Machine Learning - Sebastian Raschka
Deep Learning with Hadoop - Dipayan Dev
Deep Learning with Python - A Hands-on Introduction - Nikhil Ketkar
Artificial Intelligence - A Very Short Introduction - Margaret A.Boden
Deep Learning with Python - Francois Cholletf
Practical computer vision applications using Deep Learning with CNNs - Ahmed Fawzy Gad
Machine Learning Applications Using Python - Cases studies form Healthcare, Retail, and Finance - Pu...
Scikit-learn Cookbook Second Edition over 80 recipes for machine learning - Julian Avila & Trent Hau...
Deep Learning with Keras - Antonio Gulli & Sujit Pal
Coding Theory - Algorithms, Architectures and Application
Building Chatbots with Python Using Natural Language Processing and Machine Learning - Sumit Raj
Deep Learning with Theano - Christopher Bourez
Deep Learning from Scratch - Building with Python form First Principles - Seth Weidman
Machine Learning Mastery with Python - Understand your data, create accurate models and work project...
Fundamentals of Deep Learning - Nikhil Bubuma
Neural Networks and Deep Learning - Charu C.Aggarwal
Python Machine Learning Cookbook - Practical solutions from preprocessing to Deep Learning - Chris A...
Intelligent Projects Using Python - Santanu Pattanayak
Machine Learning with Python for everyone - Mark E.Fenner
Introduction to Machine Learning with Python - Andreas C.Muller & Sarah Guido
Deep Learning and Neural Networks - Jeff Heaton