A new edition of PyData Zurich! (7pm, 26th of June, at Digicomp Zurich)
In this meetup we will have the following exciting talks:
*Tim Head - Binder - one click sharing of your data science
When other people want to run the code of the cool data project you did last week you usually think: “Great someone cares!” and then “Oh no, now I need to play support desk till they get it running.”
The Binder project lets anyone run the contents of a git repository by clicking a link. For example try out the latest JupyterLab demo by clicking this link (https://mybinder.org/v2/gh/jupyterlab/jupyterlab-demo/master?urlpath=lab%2Ftree%2Fdemo%2FLorenz.ipynb) . Binder lets you describe the dependencies of your repository in a way that we can automatically create a Docker container from it. Removing the need for you to spend a lot of time to help others who are trying to get your code to run.
I will tell you about the Binder project, how to use it to share work, what the tools behind it are, and how you can join the team working on Binder.
Some example uses:
Reproduce and explore the journal article "Right for the Right Reasons: Training Differentiable Models by Constraining their Explanations" by Ross et al (https://mybinder.org/v2/gh/dtak/rrr/master?urlpath=lab).
Learn about "Foundations of numerical computing" (https://mybinder.org/v2/gh/ssanderson/foundations-of-numerical-computing/master?filepath=notebooks) with Scott Sanderson.
Dive into Julia Evans’ "Pandas cookbook" (https://mybinder.org/v2/gh/jvns/pandas-cookbook/master).
* Dr Marcin Pietrzyk - Opportunities and obstacles for AI adoption from the industry perspective
In this talk we will discuss opportunities, obstacles and lessons learned from working with some of the most prominent non-digital native industries. We will unveil the biggest challenges the companies struggle with while adopting AI and factors that lead to success.
* Michal Rachtan - Engineering for good - using Deep Learning to detect pneumonia on X-Ray images
Pneumonia is the world’s deadliest disease, killing two children every minute. Today, chest X-rays are the best known and available method for diagnosing pneumonia.
In this talk, we will highlight some of the challenges associated with diagnosing the disease and how machine learning can be employed to assist in the process. We will use Kaggle data to explain how the selected ML techniques and software including Convolution Neural Networks, Transfer Learning, and Tensorflow can be employed to detect the disease from raw X-Ray images. We look forward to an interactive session and to hear from you too.
and as always:
*Lightning talks - Your special 5 minutes
Every speaker gets 5 minutes to share interesting insights, projects or other fun stuff.
Claim the event and start manage its content.I am the organizer