Python Machine Learning Case Studies - Danish Haroon - E-Book

Python Machine Learning Case Studies E-Book

Danish Haroon

0,0
79,99 €

-100%
Sammeln Sie Punkte in unserem Gutscheinprogramm und kaufen Sie E-Books und Hörbücher mit bis zu 100% Rabatt.

Mehr erfahren.
Beschreibung

Embrace machine learning approaches and Python to enable automatic rendering of rich insights and solve business problems. 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 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.


Das E-Book können Sie in einer beliebigen App lesen, die das folgende Format unterstützt:

PDF

Veröffentlichungsjahr: 2017

Bewertungen
0,0
0
0
0
0
0
Mehr Informationen
Mehr Informationen
Legimi prüft nicht, ob Rezensionen von Nutzern stammen, die den betreffenden Titel tatsächlich gekauft oder gelesen/gehört haben. Wir entfernen aber gefälschte Rezensionen.