You will get customized Recommendation System/Engine using AI and Machine Learning


Project details
I design and build custom AI-powered recommendation systems that help e-commerce and marketplace platforms turn browsing behavior into real sales. Drawing on machine learning and applied data science, I create recommendation engines that learn from how customers browse, what they're interested in, and how they rate products — then use that to surface the right items at the right moment.
I build these using Python, with Keras or PyTorch for the embedding models and FAISS or Pinecone for fast, scalable similarity search — and I integrate cleanly with Shopify, WooCommerce, or a custom backend through a documented API.
Deliverables include well-structured, maintainable code, an integration-ready API, and optional cloud deployment. The goal throughout is business impact: more relevant suggestions, higher conversion rates, and stronger repeat engagement — not just a model that technically works.
Related previous works -
• Food Recommendation Engine - Correlating between user and food based on description and conditions
• Perfume Recommendation System - Recommend perfume for users profile
• Ecommerce Product Recomendation - Based on related product browse
I build these using Python, with Keras or PyTorch for the embedding models and FAISS or Pinecone for fast, scalable similarity search — and I integrate cleanly with Shopify, WooCommerce, or a custom backend through a documented API.
Deliverables include well-structured, maintainable code, an integration-ready API, and optional cloud deployment. The goal throughout is business impact: more relevant suggestions, higher conversion rates, and stronger repeat engagement — not just a model that technically works.
Related previous works -
• Food Recommendation Engine - Correlating between user and food based on description and conditions
• Perfume Recommendation System - Recommend perfume for users profile
• Ecommerce Product Recomendation - Based on related product browse
Machine Learning Tools
BERT, Keras, NLTK, NumPy, Python, PyTorch, scikit-learn, Word2vecWhat's included
| Service Tiers |
Starter
$150
|
Standard
$300
|
Advanced
$500
|
|---|---|---|---|
| Delivery Time | 1 day | 2 days | 4 days |
Number of Revisions | 0 | 0 | 0 |
Model Validation/Testing | - | - | - |
Model Documentation | - | - | - |
Data Source Connectivity | - | - | - |
Source Code |
Optional add-ons
You can add these on the next page.
Additional Model Variation
(+ 1 Day)
+$150
Model Validation/Testing
(+ 1 Day)
+$100
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AE
Abdullah E.
May 1, 2025
30 minute consultation
AE
Abdullah E.
Apr 22, 2025
30 minute consultation
BK
Benjamin K.
Apr 7, 2025
AI/ML Expert Needed for Live Data Noise Reduction
EK
Eric K.
Mar 18, 2025
Seeking Data Scientists with ETL, ML, Python experience / gsmlsmus-2025-q1
Sadidul did a great job on ETL and ML tasks. We’d be happy to work with this freelancer again.
SA
Sajjad A.
Mar 18, 2025
Computer vision expert needed
I had a great experience working with Mr Sadidul Islam on an OCR project. He is highly skilled, efficient, and delivered accurate results while optimizing performance. Communication was smooth, and he went above and beyond to ensure the project met all requirements. Highly recommended for any OCR or data extraction.
About Sadidul
Machine Learning Expert - Computer Vision, LLM, & Predictive Modeling
80%
Job Success
Dhaka, Bangladesh - 6:13 am local time
Core Competencies:
- Computer Vision & OCR: Object detection (YOLO, ViT), document extraction, and structural drawing analysis using OpenCV, Tesseract, and AWS Textract.
- LLMs & Generative AI: Fine-tuning (Llama, GPT), RAG implementation, chatbots, and text-to-speech agents using Hugging Face, ChromaDB, and Pinecone.
- MLOps & Deployment: Containerizing services with Docker and deploying scalable solutions on AWS and GCP with a focus on cost optimization and low latency.
- Predictive Modeling & Recommendations: Building robust models for fintech, stock forecasting, and personalized recommendation engines.
I combine strong Python programming with deep learning frameworks (PyTorch, TensorFlow) to turn complex data into production-ready applications. Let’s discuss how I can help you build or optimize your AI infrastructure.
Skills: Python, PyTorch, TensorFlow, Hugging Face/Transformers, RAG, OpenCV, YOLO, ViT, VGG, ResNet, DocTR, Tesseract, AWS Textract, Google OCR, OpenAI API, LLAMA-3, ChromaDB, Pinecone, Docker, AWS, GCP
Types of projects I have completed in recent years -
#1 OCR / Document Extraction
- NLP expert to extract information from natural text — Extract information from images and PDFs using OCR
- Computer Vision Expert for Web App (OCR + AutoML) — Testing kit detection from images and reading test results
- NLP expert to extract information from natural text — Finding names, company names, etc. from images and PDFs
- Computer Vision Engineer for Post-Tension Structural Drawing Analysis (PDFs) — 2D drawing analysis
#2 Computer Vision
- Object Detection/Counting Project — Iron rod counting in batches using YOLOv8
- Object detection for ice hockey video — Detecting players, puck, and possession based on activity
- Mechanical Component Segmentation and Clustering — 2D drawing analysis
- AI/ML Engineer, Python/React for Skincare App — ML model integration in React Native app
#3 LLM / Generative AI
- Prototype Real-Time Text-to-Speech AI — Calling agent using OpenAI (GPT-4, Whisper), Google TTS, and Twilio
- Llama-2, Long Llama Engineer — Using open-source LLM models
- Data Engineer ML/AI — Customer care chatbot using OpenAI and LLaMA-7B
- AI Training for Foreign Language — Fine-tuning LLM models
#4 Regression / Predictive Modeling
- Cloud-based Data Scientist (AWS) — Models for fintech (NLP, Tabular)
- Stock market price prediction — Using historical data to predict future prices
- Balance/debt forecasting — Using bank statement data to predict debt and balance
#5 Recommendation Systems
- Food Recommendation Engine — Correlating users and food menu item based on description
- Similar Products based on Users Interest — Find the product a user might be interested in
- Perfume suggestion based on User Profile — Suggest existing perfumes based on users profile
Steps for completing your project
After purchasing the project, send requirements so Sadidul can start the project.
Delivery time starts when Sadidul receives requirements from you.
Sadidul works on your project following the steps below.
Revisions may occur after the delivery date.
Discuss about the input and outcome
Share required available datasets
