What is the current state of machine learning and data science in enterprises? For the second year in a row, Algorithmia have published their State of Enterprise Machine Learning report. It shows the top machine learning use cases in enterprises and what trends to look out for in the future.
The first day of ML Conference and Voice Conference 2019 started out with an exciting keynote and you can read all about it here. The speaker, Dr. Janina Loh, raised questions about the moral and ethical implications of robots in the digital age.
In the final keynote of ML Conference 2019 in Berlin, Dr. Neda Navidi dives into the topic of human-AI interaction, looking at a new approach for interactive learning. Here’s the livestream of the keynote if you couldn’t make it to Berlin this year.
In the second keynote at ML Conference 2019 in Berlin, Dr. Yonit Hoffman dives into the topic of data science: How can data science and machine learning help prevent accidents at sea that cost lives, money and environmental destruction? Here’s the livestream of the keynote if you couldn’t make it to Berlin this year.
Welcome to this year’s ML Conference and Voice Conference in Berlin! Keynote speaker Dr. Janina Loh explores the moral questions that go hand in hand with the construction and use of robots—from a critical overview of some fields of robotics to practical implications. Watch our live stream here if you couldn’t make it to Berlin this year.
Netflix often releases its internal tools to the public as open source code. The latest project to join the fray is Metaflow, a “deceptively simple” Python library for data scientists. Metaflow features integration with Amazon Web Services and includes a built-in capability to snapshot all code and data into Amazon Simple Storage Service.
The ML service Amazon CodeGuru has been released as a preview version. It provides automated code reviews—and is designed to help you find the most expensive bits of code and improve performance. Let’s see how that works and what features the new service offers.
This talk from the Machine Learning Conference gives a fun history of mining examples and presents some of the available tooling. Some of the topics we’ll be going over include embeddings, dynamic time warping, seriation, and HDBSCAN. Watch Vadim Markovtsev’s ML Conference session and come away knowing more about software development.
This down-to-earth machine learning talk from Daniel Molnar is for the underdog. What choices should you make in the vast world of machine learning and deep learning when there are so many options? Don’t base your choices on a gut feeling or product hype; use real world experience based on practical applications.
In this article, explore how a combination of artificial intelligence and machine learning can act as the brains of a smart city while simultaneously considering how a smart city experience can become more personalized without compromising the privacy of its residents. Read on to see what the advantages and disadvantages of an ML and AI-powered smart city are.
The machine learning platform TensorFlow, currently in version 2.0, is making its way toward the minor release 2.1.0: TensorFlow 2.1.0-rc0 is the first release candidate and includes some breaking changes. The upcoming version will be the last to support Python 2.7.
Chatbots are among the most popular applications of artificial intelligence, machine learning, and natural language processing, and many people are already familiar with them. Various companies are developing first prototypes to improve their customer communication and support functions. How do we begin to implement them into an industrial context?
Modern technology can help free yourself from data sampling. Current computing power has made scalability vastly and available and machine learning algorithms have made the discovery of data quality issues automated and easy. Move on from the old ways of data sampling and learn how to enter the new world of big, smart data.
As machine learning technologies become more prevalent, the risk of attacks continues to rise. Which types of attacks on ML systems exist, how do they work, and which is the most dangerous? ML Conference speaker David Glavas answered our questions.
