PyData June 2020 Virtual Meetup

6th meetup in 2020 and again we will make it remote!
We will start with the talks at 19:00.

The link to the Zoom meeting will be sent to all attendees about an hour before the meetup and there will be a YouTube live stream for those not on the zoom call.

We have two great speakers for the upcoming meetup, as well as an informative PyData break in between. Hope to you all there.

Talks:

Karol Przystalski

Computer vision methods for skin cancer recognition

Pattern recognition of images is one of the most popular approaches that is used in machine learning solutions supporting medical doctors. We show to use image processing methods to do simple image analysis to find skin cancer cases. In the next step, we use neural networks and simple white-box methods to recognize skin cancer patterns on multilevel images.

Karol Obtained a PhD degree in Computer Science in 2015 at the Jagiellonian University in Cracow. CTO and founder of Codete. Leading and mentoring teams of Codete. Working with Fortune 500 companies on data science projects. Built a research lab that is working on machine learning methods and big data solutions in Codete. Give speeches and workshops in German and English in data science with a focus on applied machine learning.

https://github.com/codete/PyData-Berlin

Andrés Ruiz (https://www.linkedin.com/in/andres-ruiz-montanez)

Introduction to Time Series Analysis and Forecast

When dealing with time as an independent variable, it is valuable to comprehend the effects that the underlying relationships among the features and time may have on our analysis. This presentation aims to introduce the main concepts behind time series analysis and to provide the audience with a basic understanding of the processes and techniques.

Initially, key definitions as stationarity, patterns, autocorrelation, and lag variables will be explored. Afterward, a brief overview of the differences and factors to take into consideration while preparing and modeling time-dependent data. And finally, a high-level overview of the most relevant models as Naïves, AR/MA and ARIMAX, traditional multiple regression approach, and Long short-term memory (LSTM) artificial recurrent neural network (RNN). The presentation focuses on the theoretical aspect of time series and will not approach the technical, and implementation aspects in depth.

Andrés is a Colombian Architect, based in Berlin while pursuing an M.Sc. in Project Management and Data Science. He is a self‐taught developer with more than 8 years of experience in the digital ecosystem and entrepreneurship. Currently working as Chief Technology Officer at Aequales, a fast-growing company dedicated to providing tools for the closing of gender gaps in the workplace through technology and data.

He is the lead developer of the Ranking PAR Platform which is a measurement tool of the gender equality conditions of organizations in Latin America. The PAR Ranking provides an internal report of gender equality to each participating company, the ability to compare itself with more than 800 of the biggest companies across the continent, and see their progress over time.

NumFOCUS Code of Conduct

Be kind to others. Do not insult or put down others. Behave professionally. Remember that harassment and sexist, racist, or exclusionary jokes are not appropriate for NumFOCUS.

All communication should be appropriate for a professional audience including people of many different backgrounds. Sexual language and imagery is not appropriate.

NumFOCUS is dedicated to providing a harassment-free community for everyone, regardless of gender, sexual orientation, gender identity, and expression, disability, physical appearance, body size, race, or religion. We do not tolerate harassment of community members in any form.

Thank you for helping make this a welcoming, friendly community for all.

If you haven't yet, please read the detailed version here:
https://numfocus.org/code-of-conduct