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

  • AWS Sagemaker
  • AWS Lamda
  • Python
  • Keras
  • React
  • Postgress SQL

    • Industry

    Cloud, Information Technology

  • region

    • Region

    USA

  • project-size

    • 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.

The Development

  • Cost Reduction
  • Predictive Analytics
  • Quick Response Time
  • Personalized Communication
  • no.-of-resources

    • No. of Developers

    04

  • time-frame

    • Time Frame

    March 2022 - July 2022

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