Browse categories
Explore
Fiverr Pro
English
$
USD
I will do data science and signal processing projects
About this Gig
Seasoned Bio-Signal Analyst: Data Science, Signal Processing & Machine Learning for EEG, fNIRS and fMRI
Drowning in noisy, unreliable recordings? I deliver expert data analysis, signal processing, and machine learning solutions built for biosignal and neuroimaging projects.
What I Do:
- EEG, fNIRS and in vitro signal cleaning, preprocessing & artifact rejection
- Time-series analysis, filtering, feature extraction & statistical modeling
- fMRI & neuroimaging workflows (preprocessing, GLM, connectivity, ICA)
- 2D/3D image processing & computer vision
- NIfTI and BIDS dataset organization and handling
- Machine learning & deep learning (classification, regression, CNN, LSTM)
- Model deployment using AWS SageMaker, Docker & REST APIs
- Clear data visualization & reproducible pipelines
My Toolkit:
- Python (NumPy, SciPy, Pandas, MNE-Python, scikit-learn, TensorFlow, PyTorch), MATLAB (EEGLAB, FieldTrip, SPM, ERPLab), AWS SageMaker, Jupyter Notebook, Git, Docker, Wavelet Transform, FFT, PCA/ICA, Nilearn, ANTs, FSL
Methods: Denoising, time-frequency & connectivity analysis, dimensionality reduction, feature engineering. You get clean code, rigorous methodology, and thorough documentation.
Let's connect!
Programming language:
Python
•
MATLAB
•
SQL
•
MLflow
•
Amazon SageMaker
Frameworks:
Scikit-learn
•
Google ML Kit
•
Keras
•
PyTorch
•
Panda
My Portfolio
FAQ
Any model deployment?
Yes! I deploy ML/DL models using AWS SageMaker, Docker, and REST APIs (Flask/FastAPI) for real-time or batch inference. From training to production-ready endpoints, I deliver scalable, reproducible deployments. Message me your use case for the best approach!
Can you sign an NDA for sensitive/medical data?
Yes, I'm glad to sign an NDA and handle sensitive or clinical data with strict confidentiality.
What if I only have a small or messy dataset?
No problem, I can work with limited or messy data and advise on best practices for cleaning and improving data quality.
