You will get a Machine Learning Model
Project details
This is a proposed professional ML system in OOP python code ready for production. The deliverable will consist of one or more trained model(s) with a prediction tool and a tool that will handle and preprocess new data when found and update the model automatically. Alternatively one may select one or more Jupyter notebooks that will perform the same tasks.
What's included $500
These options are included with the project scope.
$500
- Delivery Time 5 days
- Number of Revisions 1
- Number of Model Variations 1
- Number of Graphs/Charts 5
- Model Validation/Testing
- Model Documentation
- Data Source Connectivity
- Source Code
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About Georgios
Expert Data Scientist
Piraeus, Greece - 5:28 pm local time
I am a senior data scientist with more than 25 years of experience across statistics, econometrics, machine learning, analytical software, and financial risk. My professional background includes serving as a Chief Data Scientist and Credit Risk Manager, completing more than 70 commercial data-science engagements, building consistently all the range of credit risk models (PD, EAD, LGD, Affordability) including LLM for transactional data, credit scoring using CRA data and also contributing to research collaborations with universities in Europe and Australia.
My principal areas of expertise are:
Credit risk and lending analytics: PD and LGD modelling, affordability assessment, application and behavioural scoring, model validation, threshold optimisation, monitoring, explainability, and responsible lending.
LLMs and natural language processing: text and transaction classification, information extraction, structured outputs, prompt and model evaluation, document analysis, and workflow automation.
Time-series modelling and forecasting: statistical forecasting, machine-learning and deep-learning models, feature engineering, backtesting, model comparison, and uncertainty assessment.
Machine learning and statistical analysis: regression, classification, clustering, imbalanced learning, exploratory analysis, model interpretation, hypothesis testing, econometrics, and reproducible research.
I can support the full project lifecycle: problem definition, data-quality assessment, exploratory analysis, model development, validation, documentation, automation, and production handover.
Core technologies: Python, pandas, NumPy, scikit-learn, TensorFlow/Keras, PyTorch, FastAPI, APIs, statsmodels, XGBoost/LightGBM, NLP and transformer tools, SQL, matplotlib, and cloud-based workflows.
My deliverables are designed to be technically rigorous and practically usable: clear assumptions, reproducible code, defensible evaluation, transparent limitations, and business-oriented recommendations.
Steps for completing your project
After purchasing the project, send requirements so Georgios can start the project.
Delivery time starts when Georgios receives requirements from you.
Georgios works on your project following the steps below.
Revisions may occur after the delivery date.
Data Management
Load data and process features to be ready for further analysis.
Exploratory Data Analysis
Analyze data to discover hidden patterns and reveal insights.