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Data Science and Machine Learning with R from A-Z Course [Updated for 2021] /
Learn machine learning and data analysis from scratch with R About This Video Learn data extraction and web scraping Learn to build custom data solutions Learn automating dynamic report generation In Detail The course covers practical issues in statistical computing that include programming in R, re...
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| Formato: | Electrónico Video |
| Idioma: | Inglés |
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Packt Publishing,
2021.
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| Edición: | 1st edition. |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
| Sumario: | Learn machine learning and data analysis from scratch with R About This Video Learn data extraction and web scraping Learn to build custom data solutions Learn automating dynamic report generation In Detail The course covers practical issues in statistical computing that include programming in R, reading data into R, accessing R packages, writing R functions, debugging, profiling R code, and organizing and commenting on R code. Blending practical work with solid theoretical training, we take you from the basics of R programming to mastery. We understand that theory is important to build a solid foundation, we also understand that theory alone isn't going to get the job done so that's why this course is packed with practical hands-on examples that you can follow step by step. Even if you already have some coding experience, or want to learn about the advanced features of the R programming language, this course is for you! R coding experience is either required or recommended in job postings for data scientists, machine learning engineers, big data engineers, IT specialists, database developers, and much more. Adding R coding language skills to your resume will help you in any one of these data specializations requiring mastery of statistical techniques. By the end of the course, you'll be a professional data scientist with R and confidently apply for jobs and will feel good knowing that you have the skills and knowledge to back it up. |
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| Descripción Física: | 1 online resource (1 video file, approximately 28 hr., 51 min.) |
| ISBN: | 9781801075282 180107528X |