Machine Learning Archives

Taking Your Machine Learning from 0 to 10

Business + Management Conferences Machine Learning Machine Learning West 2018posted by Elizabeth Wallace, ODSC July 30, 2019

Madhura Dudhgaonkar is the senior director of Machine Learning at Workday Inc. She believes that it’s possible to deploy machine learning within your enterprise, but it takes a few steps to get exactly right. She loves to get into unknowns and things we haven’t tried yet,... Read more

ODSC Meetup: Automated and Interpretable Machine Learning

Conferences Machine Learning Modeling Machine Learning odsc meetupposted by Nathaniel Jermain July 25, 2019

Last week, ODSC hosted a talk by Dr. Francesca Lazzeri, Senior Machine Learning Scientist at Microsoft, on the capabilities of automated and interpretable machine learning software in Microsoft’s Azure. Notably, this talk is part of a series that covers a variety of data science topics. The... Read more

When Less is More: A Brief Story About Feature Engineering with XGBoost

Machine Learning Machine Learning rapidsposted by RAPIDS July 25, 2019

I played a minor role launching RAPIDS on Google Dataproc by refining a model that predicts taxi fare in New York City. Geographic location of passenger pick-ups and drops-offs were columns in the data. These are recorded as longitude and latitude measurements, with precision to many decimal places.... Read more

Interpretable Machine Learning – Fairness, Accountability, and Transparency in ML Systems

Machine Learning Modeling interpret machine learning models Machine Learningposted by Sayak Paul July 22, 2019

Editor’s note: Sayak is a speaker for ODSC West in San Francisco this November! Be sure to check out his talk, “Interpretable Machine Learning – Fairness, Accountability and Transparency in ML systems,” there! The problem is it is much harder to evaluate machine learning systems than... Read more

Make Sense of the Universe with Rapids.AI

Machine Learning Modeling Kaggle Machine Learningposted by RAPIDS July 9, 2019

Classification of astronomical sources in the night sky is important for understanding the universe. It helps us understand the properties of what makes up celestial systems from our solar system to the most distant galaxy and everything in between. The Photometric LSST Astronomical Time-Series Classification Challenge (PLAsTiCC) wanted... Read more

Watch: A Manager’s Guide to Starting a Computer Vision Program

Business + Management Conferences Machine Learning Modeling Accelerate AI Computer Vision Machine Learningposted by ODSC Team July 9, 2019

This talk by Ali Vanderveld provides you with a guide for data science leaders and managers who are thinking about starting a computer vision program. It will help you think through a set of sequential questions that you’re likely to encounter along the way: [Related Article:... Read more

Image Augmentation for Convolutional Neural Networks

Machine Learning Modeling Python Convolutional Neural Networks Machine Learning Pythonposted by Nathaniel Jermain June 26, 2019

Limited data is a major obstacle in applying deep learning models like convolutional neural networks. Often, imbalanced classes can be an additional hindrance; while there may be sufficient data for some classes, equally important, but undersampled classes will suffer from poor class-specific accuracy. This phenomenon is... Read more

Using RAPIDS with PyTorch

Deep Learning Machine Learning Modeling Tools & Languages Deep Learning Machine Learning rapidsposted by RAPIDS June 19, 2019

In this post we take a look at how to use cuDF, the RAPIDS dataframe library, to do some of the preprocessing steps required to get the mortgage data in a format that PyTorch can process so that we can explore the performance of deep learning on... Read more

The Empirical Derivation of the Bayesian Formula

Guest contributor Machine Learning Modeling Statistics bayseian Machine Learningposted by Jannes Klaas June 18, 2019

Deep learning has been made practical through modern computing power, but it is not the only technique benefiting from this large increase in power. Bayesian inference is up and coming technique whose recent progress is powered by the increase in computing power. We can explain the... Read more

10 Compelling Machine Learning Dissertations from Ph.D. Students

Data Science Academic Research Featured Post Academia Machine Learning Researchposted by Daniel Gutierrez, ODSC June 18, 2019

As a data scientist, an integral part of my work in the field revolves around keeping current with research coming out of academia. I frequently scour arXiv.org for late-breaking papers that show trends and fertile areas of research. Other sources of valuable research developments are in... Read more