Python Machine Learning Case Studies
Apress (Verlag)
978-1-4842-2822-7 (ISBN)
Python Machine Learning Case Studies 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 to help you decide which one best suits your needs.
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 bookis equipped with practical examples along with code snippets to ensure that you understand the data science approach to solving real-world problems.
What You Will Learn
Gain insights into machine learning concepts
Work on real-world applications of machine learning
Learn concepts of model selection and optimization
Get a hands-on overview of Python from a machine learning point of view
Who This Book Is For
Data scientists, data analysts, artificial intelligence engineers, big data enthusiasts, computer scientists, computer sciences students, and capital market analysts.
Danish Haroon currently leads the Data Sciences team at Market IQ Inc, a patented predictive analytics platform focused on providing actionable, real-time intelligence, culled from sentiment inflection points. He received his MBA from Karachi School for Business and Leadership, having served corporate clients and their data analytics requirements. Most recently, he led the data commercialization team at PredictifyME, a startup focused on providing predictive analytics for demand planning and real estate markets in the US market. His current research focuses on the amalgam of data sciences for improved customer experiences (CX).
Chapter 1: Statistics and Probability.- Chapter 2: Regression.- Chapter 3: Time series models.- Chapter 4: Classification and Clustering.- Chapter 5: Ensemble methods.
| Erscheinungsdatum | 06.11.2017 |
|---|---|
| Zusatzinfo | 99 Illustrations, color; 21 Illustrations, black and white; XVII, 204 p. 120 illus., 99 illus. in color. |
| Verlagsort | Berkley |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Themenwelt | Mathematik / Informatik ► Informatik ► Datenbanken |
| Informatik ► Programmiersprachen / -werkzeuge ► Python | |
| Mathematik / Informatik ► Informatik ► Software Entwicklung | |
| Informatik ► Theorie / Studium ► Algorithmen | |
| Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
| Mathematik / Informatik ► Informatik ► Web / Internet | |
| Schlagworte | bagging • Clustering • Data Analysys • Machine Leraning • Python • Regression • Time series modelling |
| ISBN-10 | 1-4842-2822-7 / 1484228227 |
| ISBN-13 | 978-1-4842-2822-7 / 9781484228227 |
| Zustand | Neuware |
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