Statistical Analysis with Swift

使用 Swift 进行统计分析:Apple 平台上的数据集、统计模型与预测

计算机软件

原   价:
451.00
售   价:
338.00
优惠
平台大促 低至8折优惠
发货周期:通常付款后3-5周到货!
作      者
出  版 社
出版时间
2021年11月13日
装      帧
平装
ISBN
9781484277645
复制
页      码
240
开      本
0 x 0 x 0 cm
语      种
英文
综合评分
暂无评分
我 要 买
- +
库存 30 本
  • 图书详情
  • 目次
  • 买家须知
  • 书评(0)
  • 权威书评(0)
图书简介
Work with large data sets, create statistical models, and make predictions with statistical methods using the Swift programming language. The variety of problems that can be solved using statistical methods range in fields from financial management to machine learning to quality control and much more. Those who possess knowledge of statistical analysis become highly sought after candidates for companies worldwide.
Starting with an introduction to statistics and probability theory, you will learn core concepts to analyze your data’s distribution. You’ll get an introduction to random variables, how to work with them, and how to leverage their properties in computations. On top of the mathematics, you’ll learn several essential features of the Swift language that significantly reduce friction when working with large data sets. These functionalities will prove especially useful when working with multivariate data, which applies to most information in today’s complex world.
Once you know how to describe a data set, you will learn how to create models to make predictions about future events. All provided data is generated from real-world contexts so that you can develop an intuition for how to apply statistical methods with Swift to projects you’re working on now.
You will:
• Work with real-world data using the Swift programming language • Compute essential properties of data distributions to understand your customers, products, and processes • Make predictions about future events and compute how robust those predictions are Chapter 1: Swift Primer.- Chapter 2: Introduction to Probability and Random Variables.- Chapter 3: Distributions- Chapter 4: Predicting House Sale Prices with Linear Regression.- Chapter 5: Hypothesis Testing.- Chapter 6: Statistical Methods for Data Compression.- Chapter 7: Statistical Methods in Recommender Systems.- Chapter 8: Reflections.
本书暂无推荐
本书暂无推荐
看了又看