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Author:   Jimmy Andersson
Publisher:   APress
Imprint:   APress
Edition:   1st ed.
Weight:   0.355kg
ISBN:  

9781484277645

ISBN 10:   1484277643
Pages:   214
Publication Date:   31 October 2021
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand  
We will order this item for you from a manufactured on demand supplier.

Table of Contents

Chapter 1: Swift Primer * Introduction to Swift and its pros when working with large data sets * Provided data sets and how to load them using the Decodable protocol * Higher-Order Functions (map, filter, reduce, apply) Chapter 2: Introduction to Probability and Random Variables * What is a random variable? * Sample spaces * Laws and axioms of probability * Variable Independence * Conditional probability Chapter 3: Distributions and Random Numbers * Mass and density functions * Discrete distributions * Discrete uniform distribution * Bernoulli trials * Binomial distribution * Poisson distribution * Continuous distributions * Continuous uniform distribution * Exponential distribution * Normal distribution * Implement a random number generator that samples from a given distribution Chapter 4: Predicting House Sale Prices with Linear Regression * Central tendency measures * Variance measures * Association measures * Stratification of data * Linear regression Chapter 5: Hypothesis Testing * T Testing * Null and Alternative Hypotheses * P-value * Determining sample sizes Chapter 6: Data Compression Using Statistical Methods * Measurement scales * Calculate the distribution of example data * Compute a Huffman Tree * Encode the original data in a smaller package * Decode the compressed data Chapter 7: Movie Recommendations Using Clustering * Data transformation * Similarity measurements * Simple movie recommendation system Chapter 8: Bringing It All Together * Applying to new, real-world projects * Building your data intuition

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Author Information

Jimmy M Andersson is a software engineer in the automotive industry, specializing in acquiring and visualizing real-time data collected from cars. He is also a graduate student at Chalmers University of Technology, currently working towards a master's degree in data science and artificial intelligence. Outside of work and studies, Jimmy writes software development articles focusing on the Swift programming language. He also develops the StatKit library - a collection of statistical analysis tools for Swift developers. StatKit is open-source and available for anyone who wants to incorporate statistical methods into their programs.

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