Solving the Data Scientist's Dilemma - The Cold Start Problem
How can you maximize the data science outcomes, benefits, and applications when faced with the cold start problem?
Knowledge Graphs in Financial Technology – Future or Hype
Applications of Mixed Effects Random Forests
Analyzing Space - Spatial Data Science Methods
Machine Learning Powers Better Decisions in Financial Services
A Breakthrough for Natural Language
Matrix Algorithms at Scale: Randomization and using Alchemist to bridge the Spark-MPI gap
We describe use cases from scientific data analysis that motivated the development of Alchemist and that benefit from this system.
Blockchain and AI, or future data systems must be built differently
Challenges and Opportunities in Applying Machine Learning
Introduction to Python for Data Science
We'll take a closer look at how Python can be leveraged to build effective data science workflows.
Blockchain AI, or Future Data Systems Must Be Built Differently
Engineering For Data Science
This talk will discuss Docker as a tool for the data scientist.
Introduction to Machine Learning
This talk gives a general introduction to machine learning, as well as introduces practical tools for you to apply machine learning in your research.
Enter the Matrix: Unsupervised feature learning with matrix decomposition to discover hidden knowledge in high dimensional data
Deep Learning in Real-Time
We will take a tour of different DL algorithms and applications, learn how different DL models are built, and see how to deploy DL models for real-time processing with SAS technology.
Mapping the Global Supply Chain Graph
Deploying your AI/FML investments
Applications of Deep Learning in Aerospace and Building Systems
This talk demonstrates using DBN, DAE, DRL and GAN in five different aerospace and building systems applications.
Applied Finance - The Third Culture
In this session we explore why it is important that we bridge the gap between the traditional data science cultures and applied finance.
Machine Learning for Mobile Sensing Applications
In this talk we’ll detail the kinds of sensor data available from mobile phones and other smart devices.
Deep Learning Techniques for Vision
This is an extremely hands-on course to take students from little knowledge of deep learning to comfort building vision models with Keras and TensorFlow.
Pavlov’s Sandman: Issues detecting snorers, training oneself not to snore via shock collar, war crime technicalities, and how to avoid all three
This talk is the journal of the explorations of a total novice audio analyst, seeking to correctly identify snores, and shock himself appropriately.
TRANSFER LEARNING: APPLICATIONS FOR NATURAL LANGUAGE UNDERSTANDING
This talk focuses on language related use cases for customer service, search, question answer, self-help and consumer finance. We'll also have some fun with applications of transfer learning.
Standardized Data Science: The Team Data Science Data Process - with a practical, example in Python