I will help in machine learning, ai, data analysis, and chatbot models
Electrical and Machine Learning Engineer, AI, Python C, and Cpp Expert
About this Gig
Machine Learning/AI specialist providing solutions to turn data into intelligent applications. From analysis to deployed models with a web interface.
What You'll Get:
- Data Analysis & Visualization: Clean data and deliver insights.
- Model Training & Tuning: Build custom models (neural nets, ensembles) and optimize performance.
- Validation & Optimization: Ensure robustness with testing.
- Deployment & Integration: Cloud setup (AWS, Azure, GCP) with API or web interface.
- Documentation & Code: Clean, commented code and a concise report.
- Revisions & Support: Two revisions; Gig Extras available.
Packages:
- Basic ($90): Analysis, visualization, preprocessing, simple model, testing.
- Standard ($100): Basic + hyperparameter tuning, API deployment.
- Premium ($150): Full pipeline: processing, advanced training, tuning, cloud deployment, web interface, monitoring, API, documentation.
- Let's transform your data into a powerful AI solution!
Programming language:
Python
•
MATLAB
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SQL
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Colab
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MLflow
Frameworks:
Scikit-learn
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Keras
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PyTorch
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Panda
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Other
Tools:
Jupyter Notebook
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TensorFlow
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Excel
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MLflow
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Colab
•
Other
My Portfolio
FAQ
What information do you need to get started on my project?
I’ll need a clear description of your objectives, sample datasets (or details on data sources), and any specific requirements (e.g., target metrics, preferred algorithms, deployment environment). If you have existing documentation or examples of expected outputs, please share those as well.
How long does it typically take to complete each package?
Basic ($90): 3–4 days for data analysis, visualization, preprocessing, and a simple model. Standard ($100): 5–6 days, including Basic tasks plus hyperparameter tuning and API deployment. Premium ($150): 7–9 days for the full pipeline—advanced model training, cloud deployment with web interface, mo
What types of data and models do you work with?
I handle structured and unstructured datasets (CSV, JSON, SQL databases, image and text data). Supervised learning: Regression, classification (e.g., random forests, XGBoost, neural networks) Unsupervised learning: Clustering, dimensionality reduction (e.g., K-means, PCA) D
Will I receive the source code and documentation?
Yes. Every package includes well-commented source code and a concise report covering: • Data preprocessing steps • Model architecture and training details • Performance metrics and validation results • Deployment instructions (API endpoints or web interface setup)

