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Python Machine Learning Project Behavior Analytics Machine Learning Algorithms - ClickMyProject

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Consumer Behavior Analytics using Machine Learning Algorithms
User-generated content in the form of reviews, ratings, and comments can be analyzed for greater insights for enterprise use. The analysis of such consumer behavior is helpful to understand the consumer's requirements and predict their future intentions towards the service. Through this cognitive study, E-commerce Organizations can track the usage and sentiments attached to their products and take appropriate marketing approaches to provide a personalized shopping experience for their consumers, thereby increasing their organizational profit. This paper aims to employ data-driven marketing tools, such as data visualization, natural language processing, and machine learning models that help in understanding the demographics of an organization. We also build recommender systems through collaborative filtering, neural networks, and sentiment analysis.
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Including Packages
=======================
* Base Paper
* Complete Source Code
* Complete Documentation
* Complete Presentation Slides
* Flow Diagram
* Database File
* Screenshots
* Execution Procedure
* Readme File
* Addons
* Video Tutorials
* Supporting Softwares
Specialization
=======================
* 24/7 Support
* Ticketing System
* Voice Conference
* Video On Demand *
* Remote Connectivity *
* Code Customization **
* Document Customization **
* Live Chat Support
* Toll Free Support *
Call Us:+91 967-774-8277, +91 967-775-1577
Get Discount @
User-generated content in the form of reviews, ratings, and comments can be analyzed for greater insights for enterprise use. The analysis of such consumer behavior is helpful to understand the consumer's requirements and predict their future intentions towards the service. Through this cognitive study, E-commerce Organizations can track the usage and sentiments attached to their products and take appropriate marketing approaches to provide a personalized shopping experience for their consumers, thereby increasing their organizational profit. This paper aims to employ data-driven marketing tools, such as data visualization, natural language processing, and machine learning models that help in understanding the demographics of an organization. We also build recommender systems through collaborative filtering, neural networks, and sentiment analysis.
*************************
Including Packages
=======================
* Base Paper
* Complete Source Code
* Complete Documentation
* Complete Presentation Slides
* Flow Diagram
* Database File
* Screenshots
* Execution Procedure
* Readme File
* Addons
* Video Tutorials
* Supporting Softwares
Specialization
=======================
* 24/7 Support
* Ticketing System
* Voice Conference
* Video On Demand *
* Remote Connectivity *
* Code Customization **
* Document Customization **
* Live Chat Support
* Toll Free Support *
Call Us:+91 967-774-8277, +91 967-775-1577
Get Discount @