MARC details
| 000 -LEADER |
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| fixed length control field |
02922nam a22002177a 4500 |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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| control field |
20230113165659.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
230113b ||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
9780367895860 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER |
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| Classification number |
006.312 |
| Item number |
ZHA |
| 100 ## - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Zhang, Nailong |
| 245 ## - TITLE STATEMENT |
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| Title |
A tour of data science: |
| Remainder of title |
learn R and Python in parallel |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
|---|
| Name of publisher, distributor, etc. |
CRC Press |
| Place of publication, distribution, etc. |
Boco Raton |
| Date of publication, distribution, etc. |
2021 |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
x, 206 p. |
| 365 ## - TRADE PRICE |
|---|
| Price type code |
GBP |
| Price amount |
44.99 |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
|---|
| Bibliography, etc. note |
Table of Contents<br/>Assumptions about the reader’s background<br/>Book overview <br/><br/>Introduction to R/Python Programming <br/>Calculator <br/><br/><br/>Variable and Type<br/>Functions <br/>Control flows<br/>Some built-in data structures <br/>Revisit of variables <br/>Object-oriented programming (OOP) in R/Python <br/>Miscellaneous <br/><br/><br/>More on R/Python Programming <br/>Work with R/Python scripts <br/>Debugging in R/Python <br/>Benchmarking <br/>Vectorization <br/>Embarrassingly parallelism in R/Python <br/>Evaluation strategy<br/>Speed up with C/C++ in R/Python<br/>A first impression of functional programming Miscellaneous <br/><br/><br/>data.table and pandas<br/>SQL <br/>Get started with data.table and pandas <br/>Indexing & selecting data <br/>Add/Remove/Update<br/>Group by <br/>Join <br/><br/>Random Variables, Distributions & Linear Regression <br/>A refresher on distributions <br/>Inversion sampling & rejection sampling <br/>Joint distribution & copula <br/>Fit a distribution <br/>Confidence interval<br/>Hypothesis testing <br/>Basics of linear regression <br/>Ridge regression <br/><br/>Optimization in Practice<br/>Convexity <br/>Gradient descent <br/>Root-finding <br/>General purpose minimization tools in R/Python <br/>Linear programming <br/>Miscellaneous <br/><br/><br/>Machine Learning - A gentle introduction <br/>Supervised learning <br/>Gradient boosting machine <br/>Unsupervised learning <br/>Reinforcement learning <br/>Deep Q-Networks <br/>Computational differentiation <br/>Miscellaneous <br/><br/> |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc. |
A Tour of Data Science: Learn R and Python in Parallel covers the fundamentals of data science, including programming, statistics, optimization, and machine learning in a single short book. It does not cover everything, but rather, teaches the key concepts and topics in Data Science. It also covers two of the most popular programming languages used in Data Science, R and Python, in one source.<br/><br/>Key features:<br/><br/>Allows you to learn R and Python in parallel<br/>Cover statistics, programming, optimization and predictive modelling, and the popular data manipulation tools – data.table and pandas<br/>Provides a concise and accessible presentation<br/>Includes machine learning algorithms implemented from scratch, linear regression, lasso, ridge, logistic regression, gradient boosting trees, etc.<br/>Appealing to data scientists, statisticians, quantitative analysts, and others who want to learn programming with R and Python from a data science perspective. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Python (Computer program language) |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
R (Computer program language) |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Data mining |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
Dewey Decimal Classification |
| Koha item type |
Book |