Discover the fundamentals of data science and develop the skills you need for achieving success in this important sector.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Section SECTION ONE: Getting oriented; Chapter 01: The untold history of data science; Chapter 02: Genres and flavours of analysis; Chapter 03: Data culture and the data science process; Section SECTION TWO: Getting going; Chapter 04: Data science examples in production; Chapter 05: A weekend crash course; Section SECTION THREE: Data science for clients; Chapter 06: The client, the project and the data; Chapter 07: Topic analysis; Chapter 08: Regression; Chapter 09: Classification; Chapter 10: Sentiment analysis; Section SECTION FOUR: Tools of the trade; Chapter 11: Data sources; Chapter 12: Data visualization; Chapter 13: Python + R; Chapter 14: Retrospective / prospective
Section - SECTION ONE: Getting oriented;
Chapter - 01: The untold history of data science;
Chapter - 02: Genres and flavours of analysis;
Chapter - 03: Data culture and the data science process;
Section - SECTION TWO: Getting going;
Chapter - 04: Data science examples in production;
Chapter - 05: A weekend crash course;
Section - SECTION THREE: Data science for clients;
Chapter - 06: The client, the project and the data;
Section SECTION ONE: Getting oriented; Chapter 01: The untold history of data science; Chapter 02: Genres and flavours of analysis; Chapter 03: Data culture and the data science process; Section SECTION TWO: Getting going; Chapter 04: Data science examples in production; Chapter 05: A weekend crash course; Section SECTION THREE: Data science for clients; Chapter 06: The client, the project and the data; Chapter 07: Topic analysis; Chapter 08: Regression; Chapter 09: Classification; Chapter 10: Sentiment analysis; Section SECTION FOUR: Tools of the trade; Chapter 11: Data sources; Chapter 12: Data visualization; Chapter 13: Python + R; Chapter 14: Retrospective / prospective
Section - SECTION ONE: Getting oriented;
Chapter - 01: The untold history of data science;
Chapter - 02: Genres and flavours of analysis;
Chapter - 03: Data culture and the data science process;
Section - SECTION TWO: Getting going;
Chapter - 04: Data science examples in production;
Chapter - 05: A weekend crash course;
Section - SECTION THREE: Data science for clients;
Chapter - 06: The client, the project and the data;
Chapter - 07: Topic analysis;
Chapter - 08: Regression;
Chapter - 09: Classification;
Chapter - 10: Sentiment analysis;
Section - SECTION FOUR: Tools of the trade;
Chapter - 11: Data sources;
Chapter - 12: Data visualization;
Chapter - 13: Python + R;
Chapter - 14: Retrospective / prospective
Rezensionen
"Value-packed on every page. Everything you need to break into data science is covered. Nelson also offers various technical examples through code to ensure every concept is thoroughly understood. I Highly recommend this book to both data science beginners and seasoned practitioners." Derrick Mwiti, Machine Learning Developer
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