MIT Press Essential Knowledge Data Science, (Paperback)
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A concise introduction to the emerging field of data science, explaining its evolution, relation to machine learning, current uses, data infrastructure issues, and ethical challenges.
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What Stands Out
Detalji o proizvodu
- Concise introduction to data science
- Explains data science's evolution and relation to machine learning
- Covers current uses and data infrastructure issues
- Discusses ethical challenges in data science
- Addresses the impact of big data and social media
- Reviews legal and ethical issues, data regulation, and privacy preservation
| Book format | Paperback |
| Fiction/nonfiction | Non-Fiction |
| Genre | Computing & Internet |
| Publication date | April, 2018 |
| Pages | 280 |
| Reading level | General, 18 |
| Subgenre | Data Science |
| Series title | MIT Press Essential Knowledge |
| Edition | 1 |
| Publisher | MIT Press |
| Original languages | English |
| Language | English |
| Is collectible | N |
| Binding type | Perfect Binding |
| Retail packaging | Single Piece |
| Assembled product height | 6.9 in |
| Assembled product weight | 0.55 lb (250 grams) |
| Bisac subject heading | Computers |
Who Should Buy?
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Beginners in Data Science
Ideal for individuals new to data science, providing foundational knowledge and a clear understanding of the field.
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Academics and Researchers
Useful for those in academia who need a concise overview of key data science concepts and methodologies.
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Professionals Seeking Skills
Great for professionals looking to enhance their data science skills for career advancement or transition into the field.
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Advanced Practitioners
Not suitable for individuals with extensive experience in data science; lacks advanced topics or complex theories.
OPIS PROIZVODA
MIT Press Essential Knowledge Data Science, (Paperback)
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Karakteristike i prednosti
- Concise introduction to data science and its evolution.
- Explains the relationship between data science and machine learning.
- Covers current applications in various sectors, including marketing and healthcare.
- Discusses data infrastructure challenges and ethical considerations.
- Offers insights into data regulation and privacy preservation.
- Provides principles for success in data science projects.
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