Trend classify
Overview
The client operates an eCommerce platform offering a diverse product catalog that continuously expands to meet evolving customer demands. They sought to enhance their service by implementing a machine learning-driven solution to predict product categories based on images and text descriptions, thereby improving customer experience and streamlining operations.
Technical Stack
Industry
Cloud, Information Technology
Region
USA
Project Size
Non- Disclosable
Highlights
Data Science-NLP Integration
Supervised Learning Classifier
Standardized Category Forecasting
Image Category Prediction
Challenges & Solutions
The absence of comprehensive product data and unstructured product titles posed a challenge in accurately categorizing products.
- Solution: Leveraging data science techniques, particularly Natural Language Processing (NLP), to analyze text descriptions and infer product categories, our data scientists and other development team members addressed the challenge of incomplete or unstructured product information.
Variations in product titles, including capitalization, special characters, and irrelevant words, hindered classification accuracy.
- Solution: Implementing machine learning algorithms for text-based classification, such as Dense Layers, Recurrent Layers, and Convolutional Layers, to process product descriptions and predict categories while mitigating text preprocessing challenges.
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Years of Business
Experience
Happy
Customers
Countries with
Happy Customers
Agile enabled
employees
The Development
- Cost Reduction
- Predictive Analytics
- Quick Response Time
- Personalized Communication
No. of Developers
04
Time Frame
March 2022 - Ongoing
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