Ten mentees will present the projects that they have been working on with their mentoors for the past 3 months.
I made a package, pyplot-themes, that helps make it easier to: 1. have decent looking matplotlib/pandas plots 2. have some decent color palettes 3. create your plot themes https://pypi.org/project/pyplot-themes/
We will talk to you about Nielsen's Connect Platform, our global, unified, open data ecosystem powered by Microsoft Azure and how we're building platform components using Python. Specifically, we'll deep dive into object-oriented data flows. As more and more data scientists write software beyond statistical models, object thinking from the field of programming can help them write test-able, maintainable and reusable components.
Machine Learning is something you'll see referenced very frequently now in everything from marketing materials to sales pitches, and job postings. With so much hype it can be hard to distinguish what people mean when they say Machine Learning. In this talk we will demystify Machine Learning by understanding its core concepts and applying that knowledge to real world examples. We'll explain basic concepts like linear algebra and loss functions, figure out when to use machine learning and build an ML model that we'll be able to use in real world apps. Here’s an in-depth list of what we'll cover: * What Machine Learning is and where it’s being used * How to recognize when machine learning is necessary * Math 101 * Linear Regression * Live Coding Session Salary Estimator * Q & A
Come learn about the new features in Python 3.8!
A chance for our community to remember and celebrate the life of Tanya Schlusser. Tanya has a long history at ChiPy and beyond. She was a mentor, a speaker, a writer, an education advocate, a loving daughter, and much much more. Members of the community will be invited to share their memories of Tanya.
Python is a growing choice for business applications processing sensitive user data and performing mission-critical tasks. That makes it vital for programmers to be aware of common security vulnerabilities that can undermine the Confidentiality, Integrity, and Accessibility of these Python applications. Fortunately, many of these risks can be managed with patterns for safe handling of user input as well as tools for dependency monitoring and static code analysis.