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.
Adam Ross Nelson is a data science consultant and career coach based in Washington D.C. As a consultant, he provides insights on data science, machine learning and data governance. He previously worked as a data scientist at The Common Application. Having transitioned into the data science field from his career as an attorney, he offers workshops, talks and online courses for those looking to develop their data science skills, pivot their career or improve their career trajectory.
Inhaltsangabe
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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