This practical guide provides a collection of techniques and best practices that are generally overlooked in most data engineering and data science pedagogy. A common misconception is that great data scientists are experts in the "big themes" of the discipline--machine learning and programming. But most of the time, these tools can only take us so far. In practice, the smaller tools and skills really separate a great data scientist from a not-so-great one.
Taken as a whole, the lessons in this book make the difference between an average data scientist candidate and a qualified data scientist working in the field. Author Daniel Vaughan has collected, extended, and used these skills to create value and train data scientists from different companies and industries.
With this book, you will:
Daniel Vaughan is head of data at Clip, the leading paytech company in Mexico. He's the author of Analytical Skills for AI and Data Science (O'Reilly).
Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.
Daniel Vaughan is currently the Head of Data at Clip, the leading paytech company in Mexico. He is the author of Analytical Skills for AI and Data Science (O'Reilly, 2020). With more than 15 years of experience developing machine learning and more than eight years leading data science teams, he is passionate about finding ways to create value through data and data science and in developing young talent. He holds a PhD in economics from NYU (2011). In his free time he enjoys running, walking his dogs around Mexico City, reading, and playing music.
„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.
Anbieter: WeBuyBooks, Rossendale, LANCS, Vereinigtes Königreich
Zustand: Like New. Most items will be dispatched the same or the next working day. An apparently unread copy in perfect condition. Dust cover is intact with no nicks or tears. Spine has no signs of creasing. Pages are clean and not marred by notes or folds of any kind. Artikel-Nr. rev9893277383
Anzahl: 1 verfügbar
Anbieter: World of Books (was SecondSale), Montgomery, IL, USA
Zustand: Good. Item in good condition. Textbooks may not include supplemental items i.e. CDs, access codes etc. Artikel-Nr. 00078603745
Anzahl: 3 verfügbar
Anbieter: PBShop.store US, Wood Dale, IL, USA
PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000. Artikel-Nr. WO-9781098146474
Anbieter: PBShop.store UK, Fairford, GLOS, Vereinigtes Königreich
PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000. Artikel-Nr. WO-9781098146474
Anzahl: 15 verfügbar
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
Zustand: New. In. Artikel-Nr. ria9781098146474_new
Anzahl: 2 verfügbar
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
Paperback. Zustand: Brand New. 250 pages. 9.00x7.00x0.50 inches. In Stock. Artikel-Nr. x-1098146476
Anzahl: 2 verfügbar
Anbieter: Kennys Bookstore, Olney, MD, USA
Zustand: New. 2023. 1st Edition. paperback. . . . . . Books ship from the US and Ireland. Artikel-Nr. V9781098146474
Anzahl: 2 verfügbar
Anbieter: Majestic Books, Hounslow, Vereinigtes Königreich
Zustand: New. pp. 248. Artikel-Nr. 399470763
Anzahl: 3 verfügbar
Anbieter: Speedyhen, Hertfordshire, Vereinigtes Königreich
Zustand: NEW. Artikel-Nr. NW9781098146474
Anzahl: 2 verfügbar
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Taschenbuch. Zustand: Neu. Neuware - This practical guide provides a collection of techniques and best practices that are generally overlooked in most data engineering and data science pedagogy. A common misconception is that great data scientists are experts in the 'big themes' of the discipline--machine learning and programming. But most of the time, these tools can only take us so far. In practice, the smaller tools and skills really separate a great data scientist from a not-so-great one. Artikel-Nr. 9781098146474
Anzahl: 2 verfügbar