You will get AI-Powered Hybrid Recommendation System
Project details
Boost Engagement with a Tailored Recommendation System
Looking to increase user retention, boost click-through rates, or maximize average order value? I will build a production-ready, custom AI recommendation engine tailored specifically to your platform—whether it's E-commerce, Streaming, Content, or a Marketplace.
What I Deliver:
Hybrid Recommendation Engine: Seamlessly combines Collaborative Filtering (user behavior) and Content-Based Filtering (item attributes) to deliver highly accurate, personalized suggestions.
Deep Learning (Advanced): Implements state-of-the-art Neural Collaborative Filtering (NCF) to capture complex, non-linear user-item interactions.
Cold-Start Solutions: Smart fallback strategies to handle new users and items with zero historical data.
Rigorous Evaluation: Validated using industry-standard metrics like Precision@K, Recall@K, and MAP.
Production Deployment: Clean, fully documented Python code and a ready-to-integrate REST API for real-time recommendations.
Let’s turn your data into a powerful engagement driver. Message me today to discuss your platform's specific needs!
Looking to increase user retention, boost click-through rates, or maximize average order value? I will build a production-ready, custom AI recommendation engine tailored specifically to your platform—whether it's E-commerce, Streaming, Content, or a Marketplace.
What I Deliver:
Hybrid Recommendation Engine: Seamlessly combines Collaborative Filtering (user behavior) and Content-Based Filtering (item attributes) to deliver highly accurate, personalized suggestions.
Deep Learning (Advanced): Implements state-of-the-art Neural Collaborative Filtering (NCF) to capture complex, non-linear user-item interactions.
Cold-Start Solutions: Smart fallback strategies to handle new users and items with zero historical data.
Rigorous Evaluation: Validated using industry-standard metrics like Precision@K, Recall@K, and MAP.
Production Deployment: Clean, fully documented Python code and a ready-to-integrate REST API for real-time recommendations.
Let’s turn your data into a powerful engagement driver. Message me today to discuss your platform's specific needs!
Machine Learning Tools
Apache Spark, Apache Spark MLlib, BERT, Keras, NumPy, pandas, Python, Python Scikit-Learn, PyTorch, scikit-learn, TensorFlowWhat's included
| Service Tiers |
Starter
$100
|
Standard
$220
|
Advanced
$450
|
|---|---|---|---|
| Delivery Time | 3 days | 7 days | 3 days |
Number of Revisions | 0 | 1 | 5 |
Number of Model Variations | 1 | 1 | 3 |
Model Validation/Testing | |||
Model Documentation | - | ||
Data Source Connectivity | |||
Source Code | - | - |
About Tabish
AI Engineer
Faisalabad, Pakistan - 6:52 am local time
"Hi, I'm Tabish , a data scientist passionate about uncovering insights and driving decisions with data. I specialize in machine learning, data visualization, and statistical analysis to help organizations make data-driven decisions. Let's connect and explore how data can drive your business
Steps for completing your project
After purchasing the project, send requirements so Tabish can start the project.
Delivery time starts when Tabish receives requirements from you.
Tabish works on your project following the steps below.
Revisions may occur after the delivery date.
Data Audit & Objective Alignment
I will analyze your user, item, and interaction datasets to evaluate data density and check for missing values. Together, we will define your target KPIs (e.g., Click-Through Rate, Conversion Rate) and establish the exact evaluation strategy.
Pipeline Setup & Cold-Start Strategy
I will build the data preprocessing pipeline to handle data ingestion and feature engineering. During this phase, I will implement robust baseline rules (such as popularity-based or trending items) to cleanly handle the user/item cold-start problem.