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Fiverr Pro
Nederlands
$
USD
I will build and deploy custom machine learning models on AWS
Data Scientist , Power BI Expert , AI and Machine Learning Engineer
"Hi, I’m Jamshed! I am a Data Scientist and Analytics professional passionate about turning raw data into smart decisions. I specialize in two core areas: First, Data Analytics—building interactive Po...
Over deze dienst
Looking for a reliable Machine Learning solution deployed on AWS?
I will build, train, evaluate, and deploy custom Machine Learning models using Python and AWS. Whether you need a predictive model for your business, research, or application, I will deliver a scalable and production-ready solution.
Services Included
Machine Learning model development
Data preprocessing and feature engineering
Classification and Regression models
Model evaluation and optimization
Deep Learning models
REST API development with FastAPI
AWS EC2 deployment
Streamlit demo application (if required)
Source code with documentation
Technologies
Python
Scikit-learn
TensorFlow
PyTorch
FastAPI
AWS EC2
Streamlit
Git
Jupyter Notebook
What You Will Receive
Well-structured Python code
Trained Machine Learning model
AWS deployment
API endpoint (if required)
Documentation
Deployment support
Please contact me before placing an order so we can discuss your project requirements and choose the best solution.
Programmeertaal:
Python
•
SQL
•
Colab
•
Java
•
NoSQL
Mijn portfolio
Veelgestelde vragen
Will you deploy the machine learning model for me?
Yes! In the Standard and Premium packages, I can wrap your trained Machine Learning model in a FastAPI backend so your developers can easily connect it to your application.
Do you work with text data (NLP) and LLMs?
Absolutely. I can build solutions ranging from basic text classification (like spam filters) to advanced AI agents using Large Language Models.
What if I don't have a clean dataset?
That is completely fine. Data cleaning and preprocessing are included in my services. I will handle missing values, outliers, and feature engineering before training the model.
