AI Recommendation Engine

2023
ShopSmart Inc.
GenAI
GenAI
Machine Learning
Python
Node.js
MongoDB

AI Neural Network

Intelligent recommendation matrix

Neural Active
CTR: 14.2%
Users: 2.4K
94%
Collaborative
87%
Content-Based
96%
Hybrid AI
98%
Deep Learning
99%
Neural Net
95%
ML Pipeline

Overview

Low-latency recommendations with batch and real-time features.

Outcomes

  • +14% CTR and +7% AOV on exposed cohorts.
  • Clear ownership and maintainable handoff to client teams.

The Challenge

Cold-start performance and model drift.

The Solution

Feature store with periodic retraining and A/B prompts.

Flow & UI Sketches

Neural Network Flow
I1
I2
I3
H1
H2
H3
H4
L1
L2
L3
Input Layer
User Data
Processing
Neural Networks
Output
Recommendations
Algorithm Matrix
94%
Collaborative
87%
Content-Based
96%
Hybrid
98%
Deep Learning
99%
Neural Net
95%
ML Pipeline
92%
Matrix
97%
Ensemble
Data Flow Visualization
Continuous Learning Loop
Real-time data processing and recommendation optimization

Project Details

  • Client:ShopSmart Inc.
  • Year:2023
  • Category:GenAI
  • Technologies:GenAI, Machine Learning, Python

Design System

Theme

AI Recommendation & Personalization

Color Palette

Violet (#8b5cf6) + Amber (#f59e0b)

Typography

Analytics-focused fonts, data-driven layouts, ML-oriented

Visual Style

Intelligent, data-driven, recommendation-focused with algorithm visualization

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AI Recommendation Engine | Hamid Ayub's Portfolio