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Domain-specific programming languages --- Application languages (Computer science) --- Domain-specific languages (Computer science) --- DSLs (Domain-specific programming languages) --- Little languages (Computer science) --- Macros (Domain-specific programming languages) --- Problem-oriented languages (Computer science) --- Programming languages (Electronic computers)

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Art --- art [discipline] --- site-specific works --- Buren, Daniel

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Introducing processes and applications based on a global scale, the book reveals how precision agriculture can be used in large-scale agriculture, community agriculture, and diversified farming. It includes site-specific information from a variety of information sources for planning, planting, growing, and harvesting agricultural crops. It also presents a new concept based on the control system theory that can be used to formulate systematic methods for more effective precision crop production.

Precision farming. --- Precision farming --- Agrotechnology and Food Sciences. Agricultural Engineering --- Technological innovations. --- Agricultural Engineering (General). --- Mechanization. --- Technological innovations --- Precision agriculture --- Prescription farming --- Site-specific agriculture --- Site-specific farming --- Soil specific crop management --- Agriculture --- United States.

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Understand the fundamentals of machine learning with R and build your own dynamic algorithms to tackle complicated real-world problems successfully About This Book Get to grips with the concepts of machine learning through exciting real-world examples Visualize and solve complex problems by using power-packed R constructs and its robust packages for machine learning Learn to build your own machine learning system with this example-based practical guide Who This Book Is For If you are interested in mining useful information from data using state-of-the-art techniques to make data-driven decisions, this is a go-to guide for you. No prior experience with data science is required, although basic knowledge of R is highly desirable. Prior knowledge in machine learning would be helpful but is not necessary. What You Will Learn Utilize the power of R to handle data extraction, manipulation, and exploration techniques Use R to visualize data spread across multiple dimensions and extract useful features Explore the underlying mathematical and logical concepts that drive machine learning algorithms Dive deep into the world of analytics to predict situations correctly Implement R machine learning algorithms from scratch and be amazed to see the algorithms in action Write reusable code and build complete machine learning systems from the ground up Solve interesting real-world problems using machine learning and R as the journey unfolds Harness the power of robust and optimized R packages to work on projects that solve real-world problems in machine learning and data science In Detail Data science and machine learning are some of the top buzzwords in the technical world today. From retail stores to Fortune 500 companies, everyone is working hard to making machine learning give them data-driven insights to grow their business. With powerful data manipulation features, machine learning packages, and an active developer community, R empowers users to build sophisticated machine learning systems to solve real-world data problems. This book takes you on a data-driven journey that starts with the very basics of R and machine learning and gradually builds upon the concepts to work on projects that tackle real-world problems. You'll begin by getting an understanding of the core concepts and definitions required to appreciate machine learning algorithms and concepts. Building upon the basics, you will then work on three different projects to apply the concepts of ma...

R (Computer program language) --- GNU-S (Computer program language) --- Domain-specific programming languages

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JavaScript (Computer program language) --- Domain-specific programming languages --- Object-oriented programming languages --- Scripting languages (Computer science)