Zobacz książki o podobnej tematyce

Więcej informacji o Data Science For Dummies 3e

• Dane szczegółowe
• Opis
• Ulubione w innej kategorii

Za ten zakup dostaniesz 71 punkty

Opis

Monetize your company's data and data science expertise without spending a fortune on hiring independent strategy consultants to helpWhat if there was one simple, clear process for ensuring that all your company's data science projects achieve a high a return on investment? What if you could validate your ideas for future data science projects, and select the one idea that's most prime for achieving profitability while also moving your company closer to its business vision? There is.Industry-acclaimed data science consultant, Lillian Pierson, shares her proprietary STAR Framework - A simple, proven process for leading profit-forming data science projects.Not sure what data science is yet? Don't worry! Parts 1 and 2 of Data Science For Dummies will get all the bases covered for you. And if you're already a data science expert? Then you really won't want to miss the data science strategy and data monetization gems that are shared in Part 3 onward throughout this book.Data Science For Dummies demonstrates:* The only process you'll ever need to lead profitable data science projects* Secret, reverse-engineered data monetization tactics that no one's talking about* The shocking truth about how simple natural language processing can be* How to beat the crowd of data professionals by cultivating your own unique blend of data science expertiseWhether you're new to the data science field or already a decade in, you're sure to learn something new and incredibly valuable from Data Science For Dummies. Discover how to generate massive business wins from your company's data by picking up your copy today.

Szczegóły książki

• Pełny tytuł: Data Science For Dummies 3e
• Język: Angielski
• Oprawa: Miękka
• Liczba stron: 432
• EAN: 9781119811558
• ISBN: 1119811554
• ID: 33584595
• Wydawca: John Wiley & Sons Inc
• Waga: 790 g
• Wymiary: 200 × 234 × 25 mm
• Data wydania: 11. November 2021

Ulubione w innej kategorii

---

---

---