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A practical guide to getting the most out of Excel, using it for data preparation, applying machine learning models (including cloud services) and understanding the outcome of the data analysis.
Solve real-world data problems with R and machine learning
Use artificial intelligence and machine learning on AWS to create engaging applications
Explore and master the most important algorithms for solving complex machine learning problems.
Learn the techniques and math you need to start making sense of your data
Tackle common commercial machine learning problems with Google’s TensorFlow library and build deployable solutions
Take tiny steps to enter the big world of data science through this interesting guide
Learn to leverage Amazon's powerful platform for your predictive analytics needs
If you want to find out how to use Python to start answering critical questions of your data, pick up Python Machine Learning – whether you want to get started from scratch or want to extend your data science knowledge, this is an essential and unmissable resource.
Learn about the fastest-growing open source project in the world, and find out how it revolutionizes big data analytics
This book has been created for data scientists who want to see machine learning in action and explore its real-world application. With guidance on everything from the fundamentals of machine learning and predictive analytics to the latest innovations set to lead the big data revolution into the future, this is an unmissable resource for anyone dedicated to tackling current big data challenges. Knowledge of programming (Python and R) and mathematics is advisable if you want to get started immediately.
Design, process, and analyze large sets of complex data in real time
A handy reference guide for data analysts and data scientists to help to obtain value from big data analytics using Spark on Hadoop clusters
Advance your skills in efficient data analysis and data processing using the powerful tools of Scala, Spark, and Hadoop
100 recipes that teach you how to perform various machine learning tasks in the real world
Design efficient machine learning systems that give you more accurate results
Understand the fundamentals of machine learning with R and build your own dynamic algorithms to tackle complicated real-world problems successfully
Master the art of machine learning with . NET and gain insight into real-world applications