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Machine Learning in Retail

kurs ist nicht verfügbar in Deutsch (Deutschland)

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Machine Learning in Retail

Dozent: Eoin Martyn Rando

Bei enthalten

Mehr erfahren

1 Modul

Verschaffen Sie sich einen Einblick in ein Thema und lernen Sie die Grundlagen.

Stufe Mittel

Empfohlene Erfahrung

6 Stunden zu vervollständigen

Flexibler Zeitplan

In Ihrem eigenen Lerntempo lernen

1 Modul

Verschaffen Sie sich einen Einblick in ein Thema und lernen Sie die Grundlagen.

Stufe Mittel

Empfohlene Erfahrung

6 Stunden zu vervollständigen

Flexibler Zeitplan

In Ihrem eigenen Lerntempo lernen

Kompetenzen, die Sie erwerben

Kategorie: Data Analysis
Kategorie: Data Preprocessing
Kategorie: Marketing Analytics
Kategorie: Machine Learning Algorithms
Kategorie: Web Analytics
Kategorie: Customer Insights
Kategorie: Machine Learning
Kategorie: Data-Driven Marketing
Kategorie: Customer Analysis
Kategorie: Retail Store Operations
Kategorie: Machine Learning Methods
Kategorie: Decision Tree Learning
Kategorie: Histogram
Kategorie: Applied Machine Learning
Kategorie: Unsupervised Learning

Werkzeuge, die Sie lernen werden

Kategorie: Pandas (Python Package)

Wichtige Details

Zertifikat zur Vorlage

Zu Ihrem LinkedIn-Profil hinzufügen

Bewertungen

5 Aufgaben

Unterrichtet in Englisch

91% of learners achieved a positive career outcome

Erfahren Sie, wie Mitarbeiter führender Unternehmen gefragte Kompetenzen erwerben.

Weitere Informationen zu Coursera für Unternehmen

Logos von Petrobras, TATA, Danone, Capgemini, P&G und L'Oreal

In diesem Kurs gibt es 1 Modul

Who are your customers? What are they like? How do they interact with your business? This Short Course was created to help analysts better understand their customer behaviour through the power of machine learning.

In this course, you will apply two different machine learning techniques to segment customers according to their purchasing behaviour and provide actionable insights for each group. Along the way, you'll also examine some other retail case studies, including web visitor analysis for marketing and store clustering for logistics. By the end, you'll be able to use customer purchase data to group customers using machine learning, analyse your results to extract business insights and apply multiple types of machine learning to generate business value. This course is unique because it focuses strongly on interpreting your data within a retail context and supports you in identifying opportunities for machine learning in your workplace. To be successful in this project, you should already be familiar with Python Pandas for data manipulation, filtering and aggregation. You should also have some experience with basic principles of data analysis, like histograms and summary statistics.