AI Learning Accelerator
Andy Palmer
Free

DATAOPS: ENTERPRISE DATA THAT DOESN’T SUCK

During his talk, Andy will highlights the converging factors that allow non-data native companies transform their data engineering organizations to catch up with data-native companies like Facebook, Google and Amazon.

Colin Gillespie
Free

Getting to Grips with the Tidyverse (R)

In this tutorial, we'll cover some of the core features of the tidyverse, such as dplyr (the workhorse of the tidyverse), string manipulation, linking directly to databases and the concept of tidy data.

Julien Simon
Free

DEEP LEARNING FOR DEVELOPERS

This covers concepts of Neural Networks and Deep Learning in simple terms, with minimal theory and math. Then, through code-level demos based on Apache MXNet, we're building, training and using models based on different types of networks.

Jeffrey Yau, PhD
Free

MULTIVARIATE TIME SERIES FORECASTING USING STATISTICAL AND MACHINE LEARNING MODELS

This lecture discusses the formulation Vector Autoregressive (VAR) Models, one of the most important class of multivariate time series statistical models, and neural network-based techniques.

Michael Stewart
Free

GRADIENT DESCENT, DEMYSTIFIED

Viewers will leave the talk with a better understanding of iterative optimization and a template of their own for implementing GD in Python, should they feel this would enrich their understanding.

Stephanie Kim
Free

RACIAL BIAS IN FACIAL RECOGNITION SOFTWARE

This talk will cover the basics of facial recognition and the importance of having diverse datasets when building out a model. We’ll explore racial bias in datasets using real world examples and cover a use case for developing an OpenFace model.

Max Humber
Free

DATAFY ALL THE THINGS

This session empower you to curate & create your own data sets. You’ll learn how to parse unstructured text, harvest data from interesting websites and public APIs and about capturing and dealing with sensor data.

Sihem Romdhani
Free

MACHINE LEARNING AND NATURAL LANGUAGE PROCESSING FOR DETECTING FAKE NEWS

Through use cases and examples, we will discuss the different fake news detection approaches from feature extraction to model construction. We will focus on how to leverage NLP to characterize and extract discriminative features of fake news.

Madison May
Free

EFFECTIVE TRANSFER LEARNING FOR NLP

In this talk, we explore parameter and data efficient mechanisms for transfer learning on text, and show practical improvements on real-world tasks. We demo the use of Enso, a newly open-sourced library designed to simplify transfer learning.

Dr. Jameson Toole
Free

Artificial Intelligence at the Edge - Jameson Toole - ODSC Meetup

Maksim Pecherskiy
Free

Building Data Science Infrastructure at the City of San Diego

Find out what type of data has city has, how a city uses its data to improve the lives of its residents and more.

Ruben Kogel
Free

User Segmentation in the Real World - A Practical Guide for Data Analysts

Ruben Kogel of VSCO walks through a logical methodology in how data analysts can approach user segmentation.

Alex Peattie
Free

The Magic of Dimensionality Reduction

Voted one of the best talks at ODSC Europe 2017. Dimensionality reduction is one of the most crucial tools in a data scientists’ toolbox, and modern tools can yield truly magical results.

Alan Rutter
Free

Telling Stories with Data

Data visualisation offers a brilliant way of bringing the raw numbers to life. This tutorial will introduce an audience-centred approach to visualising data.

Joel Grus
Free

Using AI to Answer Questions

AI expert, Joel Grus on AI systems that have a deeper understanding of the world and can demonstrate understanding through questioning and answering.

Mariya Yao
Free

The State of Conversational AI

This exceptional talk gives a technical overview & review of current state-of-the-art deep learning & NLP tactics for chatbots and conversational interfaces

Javier Rey
Free

Building an Object Detection Toolkit in Tensorflow

In this talk, we will discuss how state of the art object detection techniques work. Moreover, we will explore an implementation of an open source Python object detection toolkit based on TensorFlow

Scott Lundberg
Free

Interpreting Predictions from Complex Models

With large modern datasets the best accuracy is often achieved by complex models even experts struggle to interpret. Here, we present a unified framework for interpreting predictions, namely SHAP (SHapley Additive exPlanations)

Barton Poulson
Free

Data science for the 99%

Many small companies such as start-ups may never have a data science team. Learn ways in which this neglected majority can benefit from data science.

Jack Hidary
Free

Application of AI and Data Science in the Medical World

Learn how AI is having a profound impact in the medical world

Delaney Granizo-Mackenzie
Free

Dealing with Overfitting When Crowdsourcing Financial Alpha

Quantopian is attempting to change Fnancial services by allowing anybody to research and design trading strategies.

Kaz Sato
Free

Advancing large-scale neural network predictions

Use BigQuery for deep learning to "democratize enterprise data"

Kirill Eremenko
Free

Machine Learning For Beginners

This excellent primer teaches you the difference between AI, machine learning, and deep learning and also the basics of essential models in all three.

Ronald Bodkin
Free

Artificial Intelligence in the Enterprise

Accomplished AI expert Ronald Bodkin explains why AI is so hot, details enterprise use cases, and given you insights on how to get started on your AI journey