Data science from scratch : [first principles with Pylon] /
"Data science libraries, frameworks, modules, and toolkits are great for doing data science, but they're also a good way to dive into the discipline without actually understanding data science. In this book, you'll learn how many of the most fundamental data science tools and algorith...
Guardado en:
| Autor principal: | |
|---|---|
| Formato: | Libro |
| Lenguaje: | Inglés |
| Publicado: |
Sebastopol, CA :
O'Reilly Media,
2015.
|
| Edición: | 1st ed. |
| Materias: | |
| Aporte de: | Registro referencial: Solicitar el recurso aquí |
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| 001 | 990000645490204151 | ||
| 005 | 20180327175251.0 | ||
| 008 | 150828s2015 caua b 001 0 eng d | ||
| 020 | |a 9781491901427 | ||
| 020 | |a 149190142X | ||
| 035 | |a (OCoLC)000064549 | ||
| 035 | |a (udesa)000064549USA01 | ||
| 035 | |a (OCoLC)919314976 | ||
| 035 | |a (OCoLC)990000645490204151 | ||
| 040 | |a U@S |b spa |c U@S | ||
| 049 | |a U@SA | ||
| 050 | 4 | |a QA76.73.P98 |b G78 2015 | |
| 100 | 1 | |a Grus, Joel. | |
| 245 | 1 | 0 | |a Data science from scratch : |b [first principles with Pylon] / |c Joel Grus. |
| 250 | |a 1st ed. | ||
| 260 | |a Sebastopol, CA : |b O'Reilly Media, |c 2015. | ||
| 300 | |a xvi, 311 p. : |b il. ; |c 24 cm. | ||
| 500 | |a Subtítulo tomado de la cubierta. | ||
| 504 | |a Incluye referencias bibliográficas e índice. | ||
| 505 | 0 | |a Introduction -- A crash course in Python -- Visualizing data -- Linear algebra -- Statistics -- Probability -- Hypothesis and inference -- Gradient descent -- Getting data -- Working with data -- Machine learning -- k-Nearest neighbors -- Naive bayes -- Simple linear regression -- Multiple regression -- Logistic regression -- Decision trees -- Neural networks -- Clustering -- Natural language processing -- Network analysis -- Recommender systems -- Databases and SQL -- MapReduce -- Go forth and do data science. | |
| 520 | |a "Data science libraries, frameworks, modules, and toolkits are great for doing data science, but they're also a good way to dive into the discipline without actually understanding data science. In this book, you'll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with hacking skills you need to get started as a data scientist. Today's messy glut of data holds answers to questions no one's even thought to ask. This book provides you with the know-how to dig those answers out." --Contratapa. | ||
| 650 | 0 | |a Python (Computer program language) | |
| 650 | 0 | |a Database management. | |
| 650 | 0 | |a Data structures (Computer science) | |
| 650 | 7 | |a Python (Lenguaje de programación (Computadoras)) |2 UDESA | |
| 650 | 7 | |a Administración de base de datos (Computación) |2 UDESA | |
| 650 | 7 | |a Estructuras de datos (Computación) |2 UDESA | |