rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Python Machine Learning Case Studies
    sub title: Five Case Studies for the Data Scientist
  name:
    name part: Haroon, Danish.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: xxu
    date issued: 2017
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XVII, 204 p. 120 illus., 99 illus. in color. online resource.
  abstract: Embrace machine learning approaches and Python to enable automatic rendering of rich insights. The book uses a hands-on case study-based approach to crack real-world applications to which machine learning concepts can be applied. These smarter machines will enable your business processes to achieve efficiencies on minimal time and resources. Python Machine Learning Case Study takes you through the steps to improve business processes and determine the pivotal points that frame strategies. You’ll see machine learning techniques that you can use to support your products and services. Moreover you’ll learn the pros and cons of each of the machine learning concepts presented. By taking a step-by-step approach to coding in Python you’ll be able to understand the rationale behind model selection and decisions within the machine learning process. The book is equipped with practical examples along with code snippets to ensure th at you understand the data science approach to solving real-world problems. You will: Gain insights into machine learning concepts Work on real-world applications of machine learning Get a hands-on overview to Python from a machine learning point of view.
  table of contents: Chapter 1: Statistics and Probability -- Chapter 2: Regression -- Chapter 3: Time series models -- Chapter 4: Classification and Clustering -- Chapter 5: Ensemble methods.
  note: by Danish Haroon.
  subject:
    topic: Computer science
  subject:
    topic: Computer programming
  subject:
    topic: Programming languages (Electronic computers)
  subject:
    topic: Database management
  subject:
    topic: Computers
  subject:
    topic: Computer Science
  subject:
    topic: Computing Methodologies
  subject:
    topic: Python
  subject:
    topic: Big Data
  subject:
    topic: Programming Languages, Compilers, Interpreters
  subject:
    topic: Programming Techniques
  subject:
    topic: Database Management
  classification: QA75.5-76.95
  classification: 006
  related item:
    title info:
      title: Springer eBooks
  identifier: 9781484228234
  identifier: http://dx.doi.org/10.1007/978-1-4842-2823-4
  record info:
    record creation date: 171028
    record change date: 20171028172746.0
    record identifier: 978-1-4842-2823-4