Data Science Milan #001

Generative AI is the hype of the moment, and we are shooted by news and videos. McKinsey has written an economic impact report about this topic.

Generative AI could produce operational benefits in a handful of use cases:

-Customer operations: Improving customer and agent experiences

-Marketing and sales: Boosting personalization, content creation, and sales productivity

-Software engineering: Speeding developer work as a coding assistant

-Product R&D: Reducing research and design time, improving simulation and testing

Main impacts in the industry are estimated to be in high tech, banking, and pharmaceutical and medical products.

Look at the report

Data?Science?Milan?events

Upcoming:?On June 27th, 2023, Ivan Nardini, Ivan Vigorito and Domenico Vitarella will speak about Generative AI.?

Ivan will speak about LangChain, a framework that simplifies building applications with large language models (LLMs), and show to use it with Vertex Generative AI on Google Cloud. The other speakers will share a case study of using LangChain with PALM 2 for knowledge base Q&A in Generali.

Enroll to the event

TinyML

In this talk Pietro Montino spoke about TinyML, a core technology of modern IoT systems where data are analyzed close to where they are collected,?with benefits for energy efficiency, latency, privacy, and cost.

Explainable AI in the Banking Industry - Application of DevOps and MLOps towards digital automation in banking use cases

In the first talk Ilaria Bordino, discussed explainable AI in the banking industry, emphasizing the need for AI systems that amplify human capabilities and incorporate ethical principles. She mentioned popular methods like LIME and SHAP for model explainability and introduced the concept of counterfactual explanations.

In the second talk, Bhaskar Chakraborty explained the challenges faced in developing ML applications for automating banking workflows, such as document classification and information extraction. Bhaskar emphasized the role of DevOps in addressing these challenges by automating the continuous integration (CI) and continuous delivery (CD) processes. He explored the ML lifecycle, including data ingestion, cleaning, validation, model development, and serving.?

Watch youtube video here

Introduction to energy disaggregation with NILM

In this talk, Carlo Della Quercia discussed the topic of analysis of energy consumption data and highlights the benefits of such analysis, including energy and cost savings, as well as environmental reasons.

Specifically, it focused on the Non-Intrusive Load Monitoring (NILM) technique which makes it possible to extract the power consumption of individual home appliances starting from aggregated power reading for the house.?

Watch youtube video here

Knowledge section

TinyML community - web page

TinyML at MIT - web page

TinyMLedu, a website with educational resources, projects and more - web page

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We are also very happy if you are interested in being a speaker or if you want to share your expertise or experience with the?Data?Science?Milan?community!!!

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