Hedil Ben Hassine

Intervene with the client in the event of a software or hardware problem. Quickly perform an accurate diagnosis in order to provide one or more solutions to the client as soon as possible.

Data Collection and Preparation: Retrieving, cleaning, and preprocessing data from various sources. Exploratory Data Analysis: Identifying trends and visualizing data. Model Building: Implementing machine learning algorithms (logistic regression, random forests, neural networks). Model Evaluation: Using metrics (accuracy, F1-score, AUC-ROC) and cross-validation. Optimization and Deployment: Optimizing hyperparameters and deploying models in production.

Collecting data from various sources, such as databases and Excel files. Creating scripts or SQL queries to extract relevant data. Processing and analyzing data to identify possible improvements. Developing dashboards, reports, and visuals.