The idea is to identify Machine Learning techniques that are appropriate to the existing framework of the company and industry. The main steps of Data Science Methodology will be applied: -       Data Preprocessing with a focus on handling missing values, outliers, and noise. -       Exploratory Data Analysis in order to uncover patterns, correlations, and potential anomalies within the data.-       Model Development: unsupervised/supervised learning, neural networks, basic linear models-       The final step includes translating the results to comprehensive reports and visualizations to communicate them and provide recommendations.Additional topics can be included.  

Collaborating with a student on a machine learning-focused master's thesis can bring new opportunities for innovation, research-driven insights, and access to emerging talent in the field. This partnership can result in novel solutions, a better understanding of challenges, and skill transfer. Machine Learning techniques may lead to cost savings, prototyping benefits. Depening on industry and chosen subject, it can reduce manual tasks, improve the time management and increase revenue.

I have a big interest in the Data Science field as it is in constant development. Besides that, I see a huge potential of Machine Learning being applied in different sectors.Particular interest for industries like:- Engineering - Energy sector- Sustainability- Biology/ Chemistry- Medical industry

My thesis partner and I bring to the table a diverse and capable team, unwavering determination, and strong problem-solving and communication skills; expertise Data science, Visualization, Predictive Analytics, Machine Learning, NLP, Big Data Management. Thus, we would like to have more practical experience in solving real-world problems, task in which you can help us succeed.Our partnership promises valuable, actionable insights and solutions that can drive innovation within your organization.