Video schedule

Over the course of the next 3 months, you can take a trip down memory lane and experience the presentations you attended or the ones you missed due to conflicting presentations. Videos of the presentations will be posted on InfoQ.com or on the InfoQ YouTube channel. Below you can find the publication calendars:

INFOQ SCHEDULE
WEEK OF SESSION PRESENTER
7 MAY
  1. Machine Learning Pipeline for Real-Time Forecasting @Uber Marketplace
  2. Counterfactual Evaluation of Machine Learning Models
  • Chong Sun & Danny Yuan
  • Michael Manapat
14 MAY
  1. Developing Data and ML Pipelines at Stitch Fix
  2. Counting is Hard: Probabilistic Algorithms for View Counting at Reddit
  3. Inside a Self-Driving Uber
  • Jeff Magnusson
  • Krishnan Chandra
  • Matt Ranney
21 MAY
  1. The Black Swan of Perfectly Interpretable Models
  2. Data Pipelines for Real-time Fraud Prevention at Scale
  3. pDB: Scalable Prediction Infrastructure with Precision and Provenance
  4. Self-racing Using Deep Neural Networks: Lap 2
  • Mayukh Bhaowal & Leah McGuire
  • Mikhail Kourjanski
  • Balaji Rengarajan
  • Jendrik Joerdening & Anthony Navarro
28 MAY
  1. Liquidity Modeling in Real Estate Using Survival Analysis
  2. Deep Learning for Science
  3. End-to-End ML without a Data Scientist
  • Xinlu Huang & David Lundgren
  • Prabhat
  • Holden Karau
4 JUN
  1. TensorFlow: Pushing the ML Boundaries
  2. Interpretable Machine Learning Products
  3. Understanding ML/DL Models using Interactive Visualization Techniques
  • Magnus Hyttsten
  • Mike Lee Williams
  • Chakri Cherukuri
11 JUN
  1. Understanding Software System Behavior with ML and Time Series Data
  2. Gimel: PayPal's Analytics Data Platform
  3. Analyzing & Preventing Unconscious Bias in Machine Learning
  • David Andrzejewski
  • Deepak Chandramouli
  • Rachel Thomas
18 JUN
  1. Streaming SQL to Unify Batch & Stream Processing W/ Apache Flink @Uber
  2. Simplifying ML Workflows With Apache Beam
  • Shuyi Chen & Fabian Hueske
  • Tyler Akidau
YOUTUBE SCHEDULE
WEEK OF SESSION PRESENTER
23 APR
  1. Panel: Building a Data Science Capability (Live Recording of The InfoQ Podcast)
  • Wes Reisz & Charles Humble & Sid Anand & Stephanie Yee & Matei Zaharia & Soups Ranjan
30 APR
  1. Introduction to Forecasting
  • Franziska Bell
7 MAY
  1. NVIDIA Jetson
  2. Two Effective Algorithms for Time Series Forecasting
  • Dana Sheahen
  • Danny Yuan
14 MAY
  1. When Do You Use ML vs. a Rules Based System?
  2. PyTorch by Example
  • Soups Ranjan
  • Jendrik Joerdening
21 MAY
  1. Tooling & Setup for My Neural Network
  2. A/B Testing for Logistics: It All Depends
  • Martin Gorner
  • Jingjie Xiao
28 MAY
  1. TensorBoard: Visualizing Learning
  2. Serverless for Data Science
  • Chi Zeng
  • Mike Lee Williams
4 JUN
  1. Continuous Delivery for AI Applications
  2. Transmogrification: The Magic of Feature Engineering
  • Asif Khan
  • Mayukh Bhaowal & Leah McGuire
11 JUN
  1. Building (Better) Data Pipelines with Apache Airflow
  2. pDB: Abstraction for Modeling Predictive Machine Learning Problems
  • Sid Anand
  • Balaji Rengarajan
18 JUN
  1. The Basics of ROS Applied to Self-Driving Cars
  2. Building a Security System with Image Recognition & an Amazon DeepLens
  • Anthony Navarro
  • Jeremy Edberg
25 JUN
  1. JupyterLab: The Next Generation Jupyter Web Interface
  2. Machine Learning: Predicting Demand in Fashion
  • Jason Grout
  • Ritesh Madan
2 JUL
  1. Tensorflow Jumpstart
  2. Basics of Deep Learning: No Math Required
  • Magnus Hyttsten
  • Roland Meertens
9 JUL
  1. Detecting Similar Id Documents Using Deep Learning
  2. Deep Learning for Language Understanding (at Google Scale)
  • Burkay Gur
  • Anjuli Kannan
16 JUL
  1. Gimel: Commoditizing Data Access
  2. A Whirlwind Overview of Apache Beam
  • Romit Mehta
  • Eugene Kirpichov
23 JUL
  1. Optimizing Spark
  2. (Past), Present, and Future of Apache Flink
  • Greg Novak
  • Aljoscha Krettek
Note: These dates are subject to change without notice.