PyLadies Hyderabad 3rd meetup (women only event)

PyLadies Hyderabad chapter is back with its another meetup. This time we have two awesome speakers.

NOTE : BOTH TALKS ARE HANDS-ON

Talk 1:
Title - Introduction to Machine Learning with H2O in Python
Speaker Name - Parul Pandey
Abstract - H2O is an open-source, in-memory, distributed, fast, and scalable machine learning and predictive analytics platform that allows you to build machine learning models on big data and provides easy productionalization of those models in an enterprise environment.

This talk aims to demonstrate the basic usage of H2O with worked examples in Python.

Agenda -H2O machine learning platform & algorithms -H2O + Python API -Basic Extract, Transform and Load (ETL) procedures -Worked examples: classification and regression.

Pre-requisites

• Some basic knowledge of machine learning.
• Familiarity with Python.
• Jupyter Notebook installed on your local machine with H2O-3 installed.
• If you do not have H2O-3, you can follow the installation guide on the H2O Documentation page

Bio: Parul is a Data Science Evangelist at H2O.ai. She combines Data Science, evangelism and community in her work. Her emphasis is to spread the information about H2O and Driverless AI to as many people as possible, She is also an active writer and has contributed towards various national and international blog sites. Additionally, she also leads the WiMLDS's Hyderabad chapter which aims to promote gender diversity in the field of Machine Learning and Data Science.

Talk 2:

Title - Interactive web applications with Dash
Speaker Name - Madhu

Abstract - Dash[0] is an open-source python framework by Plotly that lets you build web applications using pure python (no JavaScript needed!). Dash is built on top of flask and react and is really extensible - it is possible to create custom components based on community-built react components. It is also possible to integrate Dash components into an existing flask application.
In this talk, we will build a simple Dash app and explore its advantages and limitations. We will also take a look at how Dash works from the inside and why it's so easy to extend. We'll then use this knowledge to build a custom dash component.
Here are a few resources to show what's possible with Dash -

a) Support Vector Machine Explorer [1]
b) Yield Curve Analysis [2]
c) Dash docs - Dash's docs themselves are written with Dash! [3]

Prerequisites - Python, minimal knowledge of React

Speaker Bio - I'm a software engineer at D.E.Shaw, working on improving the Jupyter experience for quants and recently started exploring web application development. I'm a contributor to the JupyterLab[4] project. I love exploring the internals of open source projects.

[o] - https://github.com/plotly/dash
[1] - https://dash-gallery.plotly.host/dash-svm/
[2] - https://dash-gallery.plotly.host/dash-yield-curve/
[3] - https://dash.plot.ly/
[4] - https://github.com/jupyterlab/jupyterlab

Please note it's a women-only event.