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02550nmm a2200385 u 4500 |
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EB001907804 |
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EBX01000000000000001070706 |
| 005 |
00000000000000.0 |
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cr||||||||||||||||||||| |
| 008 |
210123 ||| eng |
| 050 |
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4 |
|a QA76.9.D343
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| 100 |
1 |
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|a Salcedo, Jesus
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| 245 |
0 |
0 |
|a Advanced statistics and data mining for data science
|c Jesus Salcedo
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| 260 |
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|a [Place of publication not identified]
|b Packt
|c 2018
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| 300 |
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|a 1 streaming video file (2 hr., 53 min., 29 sec.)
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| 653 |
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|a Data Mining
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| 653 |
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|a Machine learning / http://id.loc.gov/authorities/subjects/sh85079324
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| 653 |
|
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|a Statistics / http://id.loc.gov/authorities/subjects/sh85127580
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| 653 |
|
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|a Quantitative research / fast / (OCoLC)fst01742283
|
| 653 |
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|a Data mining / fast / (OCoLC)fst00887946
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| 653 |
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|a Apprentissage automatique
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| 653 |
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|a Data mining / http://id.loc.gov/authorities/subjects/sh97002073
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| 653 |
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|a Statistics / fast / (OCoLC)fst01132103
|
| 653 |
|
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|a Quantitative research / http://id.loc.gov/authorities/subjects/sh2007000909
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| 653 |
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|a Exploration de données (Informatique)
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| 653 |
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|a Recherche quantitative
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| 653 |
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|a Machine learning / fast / (OCoLC)fst01004795
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| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b OREILLY
|a O'Reilly
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| 500 |
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|a Title from title screen (viewed February 28, 2018). - Publication date from resource description page
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| 856 |
4 |
0 |
|u https://learning.oreilly.com/videos/~/9781788830348/?ar
|x Verlag
|3 Volltext
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| 082 |
0 |
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|a 001.42
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| 082 |
0 |
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|a 000
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| 082 |
0 |
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|a 519.5
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| 520 |
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|a "Data Science is an ever-evolving field. Data Science includes techniques and theories extracted from statistics, computer science, and machine learning. This video course will be your companion and ensure that you master various data mining and statistical techniques. The course starts by comparing and contrasting statistics and data mining and then provides an overview of the various types of projects data scientists usually encounter. You will then learn predictive/classification modeling, which is the most common type of data analysis project. As you move forward on this journey, you will be introduced to the three methods (statistical, decision tree, and machine learning) with which you can perform predictive modeling. Finally, you will explore segmentation modeling to learn the art of cluster analysis. Towards the end of the course, you will work with association modeling, which will allow you to perform market basket analysis."--Resource description page
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