Machine Learning with Python for Everyone
Engels
592
49.95
Students are rushing to master powerful machine learning techniques for improving decision-making and scaling analysis to immense datasets. Machine Learning with Python for Everyone brings together all they'll need to succeed: a practical understanding of the machine learning process, accessible code, skills for implementing that process with Python and the scikit-learn library, and real expertise in using learning systems intelligently. Reflecting 20 years of experience teaching non-specialists, Dr. Mark Fenner teaches through carefully-crafted datasets that are complex enough to be interesting, but simple enough for non-specialists. Building on this foundation, Fenner presents real-world case studies that apply his lessons in detailed, nuanced ways. Throughout, he offers clear narratives, practical "code-alongs,” and easy-to-understand images -- focusing on mathematics only where it's necessary to make connections and deepen insight.

- All students need to succeed in data science with Python: process, code, and implementation

- Students will understand the machine learning process, leverage the powerful Python scikit-learn library, and master the algorithmic components of learning systems

- Integrates clear narrative, carefully designed Python code, images, and interesting, intelligible datasets



All you need to succeed in data science with Python: process, code, and implementation

- Understand the machine learning process, leverage the powerful Python scikit-learn library, and master the algorithmic components of learning systems

- Integrates clear narrative, carefully designed Python code, images, and interesting, intelligible datasets

- For wide audiences of analysts, managers, project leads, statisticians, developers, and students who want a quick jumpstart into data science



0 | 0

  • : Mark Fenner
  • : Pearson Education
  • : 9780134845623
  • : Engels
  • : Paperback
  • : 592
  • : december 2019
  • : 928
  • : 178 x 231 x 28 mm.
  • : Addison-Wesley Data & Analytics Series
  • : Gegevensanalyse