Tag Machine Learning

Distributed Deep Learning with Will Constable

http://traffic.libsyn.com/sedaily/Distributeddeeplearning.mp3Podcast: Play in new window | Download Deep learning allows engineers to build models that can make decisions based on training data. These models improve over time using stochastic gradient descent. When a model gets big enough, the training must be broken up across multiple machines. Two strategies for doing this are “model parallelism” which divides the model across machines and “data parallelism” which divides the data across multiple copies

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Video Object Segmentation with the DAVIS Challenge Team

http://traffic.libsyn.com/sedaily/objectsegmentation.mp3Podcast: Play in new window | Download Video object segmentation allows computer vision to identify objects as they move through space in a video. The DAVIS challenge is a contest among machine learning researchers working off of a shared dataset of annotated videos. The organizers of the DAVIS challenge join the show today to explain how video object segmentation models are trained and how different competitors take part in the

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Data Skepticism with Kyle Polich

http://traffic.libsyn.com/sedaily/dataskeptic_edited.mp3Podcast: Play in new window | Download With a fast-growing field like data science, it is important to keep some amount of skepticism. Tools can be overhyped, buzzwords can be overemphasized, and people can forget the fundamentals. If you have bad data, you will get bad results in your experimentation. If you don’t know what statistical approach you want to take to your data, it doesn’t matter how well you

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Poker Artificial Intelligence with Noam Brown

http://traffic.libsyn.com/sedaily/Libratus.mp3Podcast: Play in new window | Download Humans have now been defeated by computers at heads up no-limit holdem poker. Some people thought this wouldn’t be possible. Sure, we can teach a computer to beat a human at Go or Chess. Those games have a smaller decision space. There is no hidden information. There is no bluffing. Poker must be different! It is too human to be automated. The game

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Convolutional Neural Networks with Matt Zeiler

http://traffic.libsyn.com/sedaily/ClarifaiCNNs.mp3Podcast: Play in new window | Download Convolutional neural networks are a machine learning tool that uses layers of convolution and pooling to process and classify inputs. CNNs are useful for identifying objects in images and video. In this episode, we focus on the application of convolutional neural networks to image and video recognition and classification. Matt Zeiler is the CEO of Clarifai, an API for image and video recognition.

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Google Brain Music Generation with Doug Eck

http://traffic.libsyn.com/sedaily/GoogleBrain.mp3Podcast: Play in new window | Download Most popular music today uses a computer as the central instrument. A single musician is often selecting the instruments, programming the drum loops, composing the melodies, and mixing the track to get the right overall atmosphere. With so much work to do on each song, popular musicians need to simplify–the result is that pop music today consists of simple melodies without much chord

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Hedge Fund Artificial Intelligence with Xander Dunn

http://traffic.libsyn.com/sedaily/numerai_edited.mp3Podcast: Play in new window | Download A hedge fund is a collection of investors that make bets on the future. The “hedge” refers to the fact that the investors often try to diversify their strategies so that the direction of their bets are less correlated, and they can be successful in a variety of future scenarios. Engineering-focused hedge funds have used what might be called “machine learning” for a

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Multiagent Systems with Peter Stone

http://traffic.libsyn.com/sedaily/multiagent-systems_edited_1.mp3Podcast: Play in new window | Download Multiagent systems involve the interaction of autonomous agents that may be acting independently or in collaboration with each other. Examples of these systems include financial markets, robot soccer matches, and automated warehouses. Today’s guest Peter Stone is a professor of computer science who specializies in multiagent systems and robotics. In this episode, we discuss some of the canonical problems of multiagent systems, which

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Biological Machine Learning with Jason Knight

http://traffic.libsyn.com/sedaily/biodeeplearing_edited.mp3Podcast: Play in new window | Download Biology research is complex. The sample size of a biological data set is often too small to make confident judgments about the biological system being studied. During Jason Knight’s PhD research, the RNA sequence data that he was studying was not significant enough to make strong conclusions about the gene regulatory networks he was trying to understand. After working in academia, and then

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Stripe Machine Learning with Michael Manapat

http://traffic.libsyn.com/sedaily/stripeantifraud_edited.mp3Podcast: Play in new window | Download Every company that deals with payments deals with fraud. The question is not whether fraud will occur on your system, but rather how much of it you can detect and prevent. If a payments company flags too many transactions as fraudulent, then real transactions might accidentally get flagged as well. But if you don’t reject enough of the fraudulent transactions, you might not

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Technically Sentient with Rob May

http://traffic.libsyn.com/sedaily/AIwithRobMay.mp3Podcast: Play in new window | Download The impact of artificial intelligence on our everyday lives will be so profound that our modern institutions will change completely. Employment, government, romance, social norms–all of these things will be upended. To see the signs of this coming, you no longer have to read science fiction. Every week, there are blog posts, news stories, and videos chronicling our strange, exciting time. Rob May

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Where Machines Go to Learn with Auren Hoffman

http://traffic.libsyn.com/sedaily/MLwithAuren.mp3Podcast: Play in new window | Download If you wanted to build a machine learning model to understand human health, where would you get the data? A hospital database would be useful, but privacy laws make it difficult to disclose that patient data to the public. In order to publicize the data safely, you would have to anonymize it, so that a patient’s identity could not be derived from data

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Machine Learning is Hard with Zayd Enam

http://traffic.libsyn.com/sedaily/WhyMLisHard.mp3Podcast: Play in new window | Download Machine learning frameworks like Torch and TensorFlow have made the job of a machine learning engineer much easier. But machine learning is still hard. Debugging a machine learning model is a slow, messy process. A bug in a machine learning model does not always mean a complete failure. Your model could continue to deliver usable results even in the presence of a mistaken

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Deep Learning with Adam Gibson

http://traffic.libsyn.com/sedaily/DeepLearning.mp3Podcast: Play in new window | Download Deep learning uses neural networks to identify patterns. Neural networks allow us to sequence “layers” of computing, with each layer using learning algorithms such as unsupervised learning, supervised learning, and reinforcement learning. Deep learning has taken off in the last few years, but it has been around for much longer. Adam Gibson founded Skymind, the company behind Deeplearning4j. Deeplearning4j is a distributed deep

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Giphy Engineering with Anthony Johnson

http://traffic.libsyn.com/sedaily/giphy_edited.mp3Podcast: Play in new window | Download Giphy is a search engine for gifs, the short animated graphics that we see around the Internet. Giphy is also a creative platform where people create new gifs. Every search engine requires the construction of a search index, which is a data structure that responds to search queries efficiently. Since Giphy is a search engine for graphics, there is almost no text inherently

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Robots for the Elderly with Itai Mendelsohn

http://traffic.libsyn.com/sedaily/robotics_edited.mp3Podcast: Play in new window | Download Many elderly people live with unhealthy levels of isolation. Social isolation is a problem for anybody, but younger people can use technology to alleviate their isolation with tools like Skype and Facebook. How can we bridge the generational gap and give elderly people access to the same technological tools that younger people find easy to use? Voice interfaces are an important new medium

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Translation with Vasco Pedro

http://traffic.libsyn.com/sedaily/Unbabel_edited.mp3Podcast: Play in new window | Download Translation is a classic problem in computer science. How do you translate a sentence from one human language into another? This seems like a problem that computers are well-suited to solve. Languages follow well-defined rules, we have lots of sample data to train our machine learning models. And yet, the problem has not been solved–largely because languages don’t always follow rules. We have

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Medical Machine Learning with Razik Yousfi and Leo Grady

http://traffic.libsyn.com/sedaily/heartflow_edited_fixed.mp3Podcast: Play in new window | Download Medical imaging is used to understand what is going on inside the human body and prescribe treatment. With new image processing and machine learning techniques, the traditional medical imaging techniques such as CT scans can be enriched to get a more sophisticated diagnosis. HeartFlow uses data from a standard CT scan to model a human heart and understand blockages of blood flow using

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Antifraud Architecture with Josh Yudaken

http://traffic.libsyn.com/sedaily/antifraud_architecture_edited.mp3Podcast: Play in new window | Download Online marketplaces and social networks often have a trust and safety team. The trust and safety team helps protect the platform from scams, fraud, and malicious actors. To detect these bad actors at scale requires building a system that classifies every transaction on the platform as safe or potentially malicious. Since every social platform has to build something like this, Smyte decided to

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Scale API with Lucy Guo and Alexandr Wang

http://traffic.libsyn.com/sedaily/scaleapi_edited1.mp3Podcast: Play in new window | Download Some tasks are simple, but cannot be performed by a computer. Audio transcription, image recognition, survey completion–these are simple procedures that almost any human could execute, but the machine learning models have not gotten consistent enough to do them accurately. Scale is an API for human labor, created by Lucy Guo and Alexandr Wang. Similar to Amazon Mechanical Turk, Scale sends small, simple

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