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A Crash Course on Deep Learning in the Cloud
Deep learning is the newest area of machine learning and has become ubiquitous in predictive modeling. The complex brain-like structure of deep learning models is used to find intricate patterns in large volumes of data. They have substantially improved the performance of general supervised models, time series, speech recognition,... Read more
It’s About Time. Designing a Streaming Architecture For High Frequency Sensor Data
Time is precious, short, relative and complicated… especially when managing streaming applications, where calculations are performed in near-real-time. Even more challenges arise when data come from sensors and are sampled at different rates and high frequencies. Machine and deep learning algorithms are often incorporated and have different mathematical assumptions... Read more
ODSC West 2019 Preview: Get Started with Deep Learning (by Trying It!)
There are lots of ways to get started learning deep learning. The best we’ve found is to dive in with examples!  If you’re attending ODSC West, you can get your hands dirty at the 1.5-hour workshop: Practical Deep Learning. Bring your laptop for hands-on examples training a deep learning... Read more
Sequence Modelling with Deep Learning
This is a short preview post for my upcoming tutorial  “Sequence Modelling with Deep Learning” at ODSC London in November 2019. — Much of data is sequential — think speech, text, DNA, stock prices, financial transactions, and customer action histories. Our best-performing methods for modelling sequence data use deep neural networks,... Read more
Building a Natural Language Question & Answer Search Engine
Didn’t have time to read the book for the big quiz?  Why not build a system to answer the questions for you? Using the architecture pictured below we can build out a framework that can accept natural language questions as a query and answer the question using a corpus... Read more
Lots of Data, No Labels, Now What?
Editor’s Note: Interested in learning about the problem of: lots of data, no labels? See Paolo’s talk “Guiding AI to Generate the Labels we do not have with Active Learning” at ODSC West 2019. Let me tell you about a common stereotypical data story in many industries today, simplified... Read more
Why We Need Graph Analytics for Real-World Predictions
Editor’s Note: Learn more about graphs and graph analytics at the talk “Reveal Predictive Patterns with Neo4j Graph Algorithms” at ODSC West 2019 on Wednesday, October 30th. As data becomes increasingly interconnected and systems increasingly sophisticated, it’s essential to make use of the rich and evolving relationships within our... Read more
ODSC Europe 2019 Preview: Tutorial on Automated Machine Learning
This article is co-written by Joaquin Vanschoren and Pieter Gijsbers. Today’s society increasingly relies on machine learning models for complex tasks such as decision making and personalized medicine. Constructing a good machine learning model is complicated and time-intensive. Relevant data has to be collected and cleaned, features might need... Read more
Interpretable Knowledge Discovery Reinforced by Visual Methods
Editor’s Note: See Boris Kovalerchuk’s talk “Interpretable Knowledge Discovery Reinforced by Visual Methods” at ODSC West 2019. Visual reasoning and discovery have a long history. Chinese and Indians had visual proof of the Pythagorean Theorem in 600 B.C. before it was known to the Greeks. Scientists such as Bohr,... Read more
Identifying Heart Disease Risk Factors from Clinical Text
Editor’s Note: See Sudha’s talk “Identifying Heart Disease Risk Factors from Clinical Notes” at ODSC Europe 2019.  People needlessly die every single day due to preventable heart attacks. The clues are hiding right within the notes doctors and clinicians take during routine health care visits. In this presentation, we... Read more