1. Service Overview

Would you like to automate a task, analyse your data, create an interactive dashboard or develop software tailored to your business?
I offer a service for the design and development of bespoke applications in Python and R, for both the web and desktop computers.
I can build applications for businesses, entrepreneurs, students, researchers and professionals who wish to make effective use of their data.
Each application is developed to meet your specific needs, with a clear interface, tailored features and well-documented source code.
Do you have a project involving data science, machine learning or application development? Contact me to discuss your requirements and design a bespoke solution.
Machine House – Property price prediction application
Click on the link to open and use your application.

2. My developed applications:
MY ACHIEVEMENTS IN DATA SCIENCE AND MACHINE LEARNING
Discover my interactive applications developed using R Shiny and Python Streamlit.

**. Predicting house prices in Boston – Python Streamlit **
https://bostonhouse-cbz2bpoykff7hoowzdyoff.streamlit.app/

** Interactive dashboard – Python Streamlit **
https://tableaudebord-55uhnbrnfgvqermzw7ktxo.streamlit.app/

** Sonar classification using machine learning – Python Streamlit **
https://sonarclassification-t5unzm84afbh8t7zlknf9x.streamlit.app/

3. Types of applications offered
A. Web applications
Applications accessible via a web browser, depending on the chosen deployment method.
Possible features:
• Interactive dashboards.
• Import of CSV and Excel files.
• Dynamic charts and key indicators.
• Data filters and search functions.
• Statistical analyses.
• Machine learning models.
• Predictions based on new data.
• Export of results.
• Data entry forms and management interfaces.
• Database connection, depending on the project.
Technologies: Python, Streamlit, Dash, R and Shiny.
B. Desktop applications
Software that can be installed or run on a computer, primarily on Windows, depending on the project’s requirements and dependencies.
Possible features:
• Graphical user interface with menus, buttons, forms and windows.
• Import and processing of Excel, CSV and other supported file formats.
• Data management and viewing.
• Statistical calculations and automated analyses.
• Charts integrated into the interface.
• Local dashboards.
• Predictions using machine learning models.
• Export of reports and results.
• Saving of settings and results.
• Creation of a Windows executable where the technology used permits.
Possible technologies: Python with Tkinter; R with Shiny for a local application, depending on the project requirements.

NB: A desktop application and a web application are not the same. The choice of technology will depend on the desired functionality, the IT environment and installation constraints.

4. Data Science and Machine Learning Features
Depending on the package chosen, the application may include:
• Data cleaning and transformation.
• Descriptive statistics and exploratory analysis.
• Correlation studies and statistical tests.
• Linear or logistic regression.
• Time series analysis and forecasting.
• Classification and prediction.
• Segmentation and clustering.
• Model training and evaluation.
• Visualisation of results using graphs and indicators.
• Export of data, results and reports.
The methods will be selected according to the problem to be solved and the quality of the available data.

5. Packages and prices

***************************** Essential Package: €45 ***************************************************** *****
For a simple data analysis tool or a small application.
• 1 page or main screen.
• Up to 3 charts.
• Up to 3 key performance indicators (KPIs).
• Import of a CSV or Excel file.
• Descriptive analysis or simple calculations.
• Functional interface.
• Commented source code.
Delivery: 2 days.

****************************** Standard Package: 336,35 $US -********************************************************
For a more comprehensive interactive application.
• Up to 3 pages or screens.
• Up to 8 charts in total.
• Up to 6 key indicators.
• Data import and processing.
• Filters, forms or search functions.
• Statistical analysis module or basic machine learning functionality.
• Export of results to CSV or Excel.
• Source code and user guide.
Delivery: 10 days.

***************************** Premium Package: 672,69 $US ************************* *******************************
For a customised application of medium complexity.
• Up to 5 pages or screens.
• Up to 15 charts in total.
• Up to 10 key indicators.
• Customised interface.
• Data management and processing.
• Several functional modules.
• In-depth statistical analysis.
• A machine learning model, if required.
• Export of results and reports.
• Documented source code.
• Installation and user guide.
• Support with launching the application.
Delivery: 15 days.

These three packages may be used for either a web or desktop application, provided that the functionality and complexity are in line with the package. The development of more complex software will be subject to a separate quotation. These three packages may be used for either a web or desktop application, provided that the functionality and complexity are in line with the package. The development of more complex software will be subject to a separate quotation.

6. Additional options
• Database connection: from 168,17 $US.
• User authentication and management: from €60.
Prices for these options are indicative and will be confirmed depending on the technical complexity of the project.

7. Technologies used
Programming languages: Python and R.
Web applications: Streamlit, Dash and Shiny.
Desktop applications: Tkinter, CustomTkinter, PySide and PyQt in Python, as required.
Data Science: Pandas, NumPy, SciPy and R’s statistical tools.
Machine Learning: Scikit-learn and relevant packages.
Visualisation: Matplotlib, Seaborn and Plotly.

8. Why choose my service?
• Bespoke development in Python or R.
• Web applications and desktop software.
• Integration of statistical and machine learning features.
• Interfaces tailored to users’ needs.
• Well-organised and documented source code.
• Delivery accompanied by user instructions.