As an Engineering Manager at Sicara, I work on various Machine Learning projects (Computer Vision, NLP, Time Series) to be pushed to production.
During the last years, I developed a passion for data science tooling and continuous improvement in our ways of working. I am now in charge of iterating on my company’s data science technical stack.
Have you ever struggled with choosing the right tools for your Machine Learning projects? As a Lead Data Scientist in a consulting firm, I faced this challenge repeatedly and finally converged to a small set of technologies which allow to build reliable and scalable projects with a great DX (Developer Experience). In this talk, I will share the key components of my ML stack, including DVC, Streamlit, FastAPI, Terraform and other powerful tools to streamline the development and experimentation processes. Through a live demo, I will finally show you the Project Generator I’ve built to encourage adoption of these technologies and to help Data Scientists focus on the ML itself rather than the "plumbing" around it. Attendees should have a basic understanding of Python and Machine Learning concepts.