Meitiner Philip, Seneviratne Pradeeka Beginning Data Science, Iot, and AI on Single Board Computers: Core Skills and Real-World Application with the BBC Micro: Bit and Xinabox 9781484257654

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Автор: Meitiner Philip, Seneviratne Pradeeka
Название: Beginning Data Science, Iot, and AI on Single Board Computers: Core Skills and Real-World Application with the BBC Micro: Bit and Xinabox
ISBN: 9781484257654
Издательство: Springer
Классификация:

Сетевое оборудование

ISBN-10: 1484257650
Обложка/Формат: Paperback
Страницы: 316
Вес: 0.47 кг.
Дата издания: 18.07.2020
Язык: English
Издание: 1st ed.
Иллюстрации: 158 illustrations, color; 8 illustrations, black and white; xiii, 316 p. 166 illus., 158 illus. in color.
Размер: 23.39 x 15.60 x 1.75 cm
Читательская аудитория: Professional & vocational
Подзаголовок: Core skills and real-world application with the bbc micro:bit and xinabox
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: Chapter 1: Introduction to Data Science in the ClassroomChapter Goal: After reading this chapter, readers will understand the importance of measurement - they will able to measure air temperature using a thermometer and they will understand how it works. We will introduce a number of core data science concepts and how to apply them to build an experiment. Well cover some basic how-to skills for gathering and tabulating data, and we will undertake some analysis on our results. The reader will get an overview of a complete and meaningful example of applied data science, and they will be ready to explore more deeply.

Data is everywhere: Why do we measure things and what does measuring things even mean? How is this related to data science?
Using Temperature: How is temperature used in the world?
Measuring temperature: What does a thermometer do and how does it work?
Designing an experiment: We will begin to design an experiment using our thermometers to measure the temperature at different locations. We will look at factors that might have a negative impact on our experiment and well look at controlling them. We we will see the importance of validity and reliability.
Data capturing: Before our experiment commences, we will introduce the reader to the concept of data capturing - recording (tabulating) data.
Experimenting with temperature: Here we will outline the classroom activity (experiment) to collect and analyse data. We will introduce the concept of experimental design and see how it can help address issues of reliability and validity.
Analysing our results: We will introduce the concept of interrogating the data by listing a series of questions that the data set might provide insights into. In a later chapter we will look at more sophisticated analysis, for now we show how to extract some meaning / insights from the data we just collected.
Summary: Brings together all the new concepts introduced in this chapter and sets the stage for the next chapter.

Chapter 2: Data Science Goes DigitalChapter Goal: After reading this chapter, readers will understand why there is a tendency to go digital and what it means to read data digitally. We will introduce technology and coding to replicate our experiment and we will begin to explore ways that the digital approach can expand our capabilities and potential as data scientists. Well use a BBC micro: bit (or any similar device) to measure temperature, all the while looking at our experimental design and how to improve it. By the end of the chapter we will have identified the sort of hardware we need in our data science toolkit.

Making it digital: Why is everything digital? What are the types of thermometers? Explain about digital thermometers and show how they are different to analogue. How can introducing digital improve our temperature experiment from Chapter 1

Using a microprocessor to measure temperature digitally: We will use micro: bit - brief intro to microbit, including sensors that can be used for measure things causing GW (only the ambient temperature sensor).

Using the BBC micro: bit as a thermometer: Programming the micro: bit for reading the air temperature of the classroom. Use MakeCode (or MicroPython) for programming.

Analogue and digital thermometers: Reading temperature simultaneously from a micro: bit and a thermometer. Discuss differences between methods. In particular the difficulties of manual reading, need to read two things same time (thermometer or micro: bit and the clock)

Limitations of micro: bit as a standalone tool: Weve seen some limitations with microbit. By itself it provides us with too few tools. What are -ons and how are add-ons used with microprocessors, and what abou

Beginning Data Science, Iot, and AI on Single Board Computers: Core Skills and Real-World Application with the BBC Micro: Bit and Xinabox, Meitiner Philip, Seneviratne Pradeeka