Every Monday: Data Science Lunch & Learn

Online at lunch time on Crowdcast

Content

• Upcoming events
• Past events
• More events and resources

Many of the events use a Jupyter notebook to go through example code. We will mainly use Watson Studio to run these, but you can run them on any platform. To follow along in Watson Studio sign up for a free IBM Cloud account and create a Watson Studio service as described in these instructions.

Upcoming events

You?

• We are busy planning new events and creating new content and material. Suggestions on topics and speakers are always welcome! Let us know by creating an issue in this repo

Coming soon

• Trusted AI - learn about fairness and explainability
• Data exploration with Python - series using various datasets
• Deep learning series

Past events

29th March 2021: Update on COVID data analysis

• Presenter: Damiaan Zwietering - twitter
• Find all notebooks in this repo
• Replay

15th March 2021: Data Visualisation 101 with Python

• Presenter: Yamini Rao
• Replay
• Slides and Jupyter notebook

1st Feb 2021: Teaching Computers to Read (part 2)

• Presenter: Ed Shee
• Replay
• Slides and Jupyter notebook

18 Jan 2021: Staying Competitive with AutoAI

• Presenter: Gregory Bramble (AutoAI Architecture)
• Replay

14 Dec 2020: Teaching Computers to Read (part 1)

• Presenter: Ed Shee
• Replay
• Slides, notebook and data

7 Dec 2020: Deep Reinforcement Learning in Finance / Trading using Ray and RLlib

• Presenter: Romeo Kienzler
• Replay
• Repo with material used
• Gym from OpenAI

30 Nov 2020: Predict Loan Eligibility using Machine Learning Models

• Presenter: Mridul Bhandari - twitter / linkedIn
• Replay
• Notebook: https://raw.githubusercontent.com/mridulrb/Predict-loan-eligibility-using-IBM-Watson-Studio/master/loan-eligibility.ipynb
• Repo and data
• Blog and tutorial

23 Nov 2020: Learn clustering algorithms using Python and scikit-learn

• Presenter: Fawaz Siddiqi - twitter / linkedIn
• Replay
• Slides
• Handson material

Series on COVID data analysis

• Presenter: Damiaan Zwietering - twitter
• Find all notebooks in this repo
• 21 Sept 2020: Exploring COVID data with pandas (Replay)
• 5 Oct 2020: Modeling COVID data (Replay)
• 19 Oct 2020: Fitting the COVID curves (Replay)
• 2 Nov 2020: Mapping COVID projections (Replay)
• 16 Nov 2020: AMA with Damiaan (Replay)

9 Nov 2020: Automate your machine learning workflow tasks using Elyra and Kubeflow Pipelines

• Presenter: Patrick Titzler - twitter / LinkedIn
• Replay
• Slides and resources
• Elyra docs
• Blog

26 Oct 2020: Classification Models using Python and Scikit-Learn 

• Presenter: Yamini Rao
• Replay
• Notebook: https://github.com/IBMDeveloperUK/Data-Science-Lunch-and-Learn/blob/master/notebooks/Classification_models.ipynb

12 Oct 2020: Getting started with scikit-learn

• Presenter: Margriet Groenendijk
• Replay
• Notebook: https://github.com/IBMDeveloperUK/Data-Science-Lunch-and-Learn/blob/master/notebooks/20-10-12-getting-started-sklearn.ipynb

28 Sept 2020: Detecting bias in crime data - part 1

• Presenter: Margriet Groenendijk
• Replay
• Notebook: https://github.com/IBMDeveloperUK/Data-Science-Lunch-and-Learn/blob/master/notebooks/bias-in-crime-data-1-v0.ipynb

More events and resources

Call for Code Spot Challenge for Wildfires

The ultimate goal of this challenge is to predict the area of wildfires in 7 regions in Australia for February 2021 with historical wildfire and both historical and forecast weather data, so you will be predicting fires before they happened! The final submissions were on 31 January 2021.

• Landing page - http://ibm.biz/cfcsc-wildfires
• GitHub repo - https://github.com/Call-for-Code/Spot-Challenge-Wildfires
• Leaderboard - http://ibm.biz/cfcsc-wildfires-lead
• Slack workspace - http://callforcode.org/slack Channel #cfcsc-wildfires