I was fortunate enough to attend Spark + AI Summit in San Francisco in April 2019. This page contains links to all my notes from the talks I listened to.
I took notes on the talks I attended in Markdown, and those notes made up the first pieces of content of this website. The source for all of these files can be found in the Github repo for this website in the “content/posts/spark” directory.
- Predicting Communities via Graph Algorithms
- Smart Join Algorithms for Fighting Skew at Scale
- Moving a Fraud-Fighting Random Forest from sklearn to Spark with ML, MLflow, and Jupyter
- Beyond reason codes: a blueprint for human-centered, low-risk ML
- Explain Yourself: Why You Get the Recommendations You Do
- How Graph Technology is Changing AI
- High Performance Transfer Learning for Classifying Intent of Sales Engagement Emails: An Experimental Study
- Defending Deep Learning from Adversarial Attacks
- Data Agility - A Journey to Advanced Analytics and ML at Scale
- Automating Predictive Modeling at Zynga with Pandas UDFs
- Understanding Query Plans and Spark UIs
- Modular Apache Spark: Transform Your Code into Pieces