About relataly.com

Artificial Intelligence (AI) is a large area that is also rapidly evolving. Relataly.com offers a platform where you can follow trends and technologies around Machine Learning, Deep Learning, and Generative AI.

You can learn new things and share thoughts and experiences with a broader audience. If you share this idea and are enthusiastic about AI and the extensive opportunities it creates, you have come to the right place.

Relataly GitHub Repository

Florian Follonier, PhD

Zurich, CH
florian.follonier[@]relataly.com

I’m Florian, a Cloud Solution Architect for Microsoft based in Zurich. In 2020, I started a blog with the goal of providing a comprehensive resource for those looking to kick-start their Python machine learning (ML) projects. My aim was to create a centralized platform where users can access all the necessary concepts and materials related to ML, making it easier for beginners and professionals alike to get started with their projects.

The blog covers a wide range of ML topics, including but not limited to, supervised and unsupervised learning, deep learning, neural networks, and data preprocessing. I also provide tutorials, code examples, and other resources to help users understand and implement these concepts in their projects.

I’m passionate about making ML more accessible to everyone and believe that my blog can be a valuable resource for those looking to expand their knowledge in this field. Feel free to check it out and let me know if you have any feedback or suggestions.

Note: Although I work for Microsoft, my articles on this blog represent my own personal opinion.

Philipp Peron Relataly Machine Learning Blog

Philipp Peron

Munich, DE
philipp.peron[@]relataly.com

Hi, I am a student at the Technical University of Munich and currently pursuing a Master’s degree in Electrical Engineering and Information Technology. I am very passionate about Machine Learning, Software Development, and Signal Processing.

In this blog, you can find Python machine learning tutorials such as:

You can also find a series of time-series forecasting tutorials that use neural networks: