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Fiverr Pro
English
$
USD
I will build a recommendation system using python, machine learning and ai
Musfira Malik
About this gig
Looking for a custom recommendation system for movies, products, articles, music, or other content? I will build a Python-based recommendation system tailored to your dataset and requirements.
Im an AI/ML developer experienced in building content-based recommendation systems using Python, machine learning, TF-IDF, and cosine similarity.
What I offer:
Content-based recommendation engine
TF-IDF & cosine similarity
Feature engineering using multiple data features
Python implementation
Interactive Streamlit web app
Dataset integration
Clean and documented source code
Optional API integration
Use cases:
Movie recommendation systems
Product recommendation systems
Article/content recommendations
Music recommendation systems
Custom recommendation projects
My recommendation systems are lightweight, explainable, and useful when you have item information but limited user-rating history.
Why work with me?
Clean and maintainable code
Clear communication
On-time delivery
Practical and usable solutions
Have a dataset or recommendation idea? Message me and let's build it.
Get to know Musfira Malik
Musfira Malik
AI and ML Developer, Python, NLP and Data Science Specialist
- FromPakistan
- Member sinceAug 2025
- Avg. response time1 hour
Languages
Urdu, English
AI/ML developer with hands-on experience building machine learning models, NLP pipelines, and data-driven web apps in Python. I've built a movie recommendation system (TF-IDF + cosine similarity), a sentiment analysis dashboard, NLP models (NER, topic modeling, DistilBERT), customer segmentation with clustering, and deployed ML models via FastAPI. HCIA-AI certified (Huawei), currently studying Telecommunication Engineering at UET Taxila. Skilled in Python, Scikit-learn, Streamlit, FastAPI, and data visualization. I deliver clean, well-documented solutions focused on real business value.
My Portfolio
FAQ
Q1: What kind of data do I need to provide?
Ans: You can provide a dataset containing information about your items, such as movies, products, articles, music, or other content. CSV or Excel files are preferred. If you are unsure whether your dataset is suitable, message me before ordering.
Q2:Can you build recommendations based on user behavior?
Ans:Yes. This gig focuses on content-based recommendation systems. If you have user ratings, clicks, purchases, or interaction history, I can also discuss a hybrid or collaborative filtering approach as a custom requirement.
Q3:Will I get a working web app or just code?
Ans: It depends on the package you select. Basic includes the recommendation engine and source code, while Standard and Premium can include a functional Streamlit web application.
Q4:Can you integrate an external API for live data?
Ans: Yes. I can integrate suitable external APIs for live or dynamic data such as movie information, posters, images, or other content. API integration may require an additional fee depending on the requirements.
Q5:What if my dataset is small?
Ans:A small dataset can still work for a content-based recommendation system, depending on the available features. I can review your dataset and recommend the most suitable approach before development.
