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OCoLC |
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|a 9781801078436
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|a UAMI
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|a Gabrieli, Idan,
|e author.
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1 |
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|a Machine Learning for Absolute Beginners - Level 3 /
|c Gabrieli, Idan.
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250 |
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|a 1st edition.
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264 |
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|b Packt Publishing,
|c 2020.
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|a 1 online resource (1 video file, approximately 2 hr., 60 min.)
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|b 117.99
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|a Master the fundamentals of Matplotlib and Seaborn libraries and apply your skills to perform data visualization and exploratory data analysis (EDA). About This Video Grasp the fundamentals of Matplotlib and Seaborn Become confident in performing exploratory data analysis (EDA) for any data sets Get ready to visualize data using a variety of charts In Detail In the first and second course of the "Machine Learning for Absolute Beginners" training program, you have learned the fundamentals of AI and machine learning and discovered methods to pre-process the data before moving it into the machine learning algorithms. In this third and final course of the program, you will learn how to create eye-catching data visualizations using Python, Seaborn, and Matplotlib. The course starts by highlighting the learning objectives and then takes you through the fundamentals of Matplotlib and Seaborn. You will learn how to use figures, axes, customization techniques, and NumPy to perform data visualization. In the rest of this course, you will discover how to develop the ranking, proportion, trend, distribution, and correlation charts. By the end of this course, you will have the knowledge and skills to perform data visualization and exploratory data analysis (EDA) using Python, Matplotlib, and Seaborn
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542 |
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|f Packt Publishing
|g 2020
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550 |
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|a Made available through: Safari, an O'Reilly Media Company.
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0 |
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|a Online resource; Title from title screen (viewed December 30, 2020).
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590 |
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|a O'Reilly
|b O'Reilly Online Learning: Academic/Public Library Edition
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710 |
2 |
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|a O'Reilly for Higher Education (Firm),
|e distributor.
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710 |
2 |
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|a Safari, an O'Reilly Media Company.
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|u https://learning.oreilly.com/videos/~/9781801078436/?ar
|z Texto completo (Requiere registro previo con correo institucional)
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