Data science from scratch first principles with Python

With this updated second edition, you'll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch.

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Bibliographic Details
Main Author: Grus, Joel (Author)
Format: Book
Language:English
Published: Sebastopol (CA) O'Reilly Media 2019.
Edition:Second edition.
Subjects:
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Call Number :QA 76.73 .P98 .G78 2019

MARC

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264 4 |c ©2019 
300 |a xvii, 384 pages  |b illustrations  |c 24 cm. 
336 |a text  |2 rdacontent 
337 |a unmediated  |2 rdamedia 
338 |a volume  |2 rdacarrier 
500 |a Includes index. 
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 -- Deep learning -- Clustering -- Natural language processing -- Network analysis -- Recommender systems -- Databases and SQL -- MapReduce -- Data ethics -- Go forth and do data science 
520 |a With this updated second edition, you'll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. 
592 |a 0108/HL/2020  |b 25/8/2020  |c RM265.53  |h Han Lin Books 
650 0 |a Python (Computer program language). 
650 0 |a Database management. 
650 0 |a Data structures (Computer science). 
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