The 7 Best Data Science and Machine Learning Podcasts -- The Startup

#artificialintelligence

Data science and machine learning have long been interests of mine, but now that I'm working on Fuzzy.io I need to keep on top of all the news in both fields. My preferred way to do this is through listening to podcasts. I've listened to a bunch of machine learning and data science podcasts in the last few months, so I thought I'd share my favorites: Every other week, they release a 10–15 minute episode where hosts, Kyle and Linda Polich give a short primer on topics like k-means clustering, natural language processing and decision tree learning, often using analogies related to their pet parrot, Yoshi. This is the only place where you'll learn about k-means clustering via placement of parrot droppings.


athenahealth: Data Scientists

@machinelearnbot

Join us to use cutting edge machine learning to unbreak healthcare in the US. In the US, physicians face huge informational challenges – from dealing with mountains of formulaic email to wrestling with arcane insurance rules to finding at-risk patients in their large client pools. Athenahealth's Data Science group is using advanced machine learning and AI to develop a new generation of smart tools that can help physicians by reducing their paperwork, finding at-risk patients, providing key information at the right time, and overall allowing physicians to focus on what's important: spending time with patients. We're seeking experienced data scientists who love machine learning and complex data and who care about making a positive impact on the world by fielding real ML-driven systems. Positions are available at multiple levels of seniority.


Better HMM-Based Articulatory Feature Extraction with Context-Dependent Model

AAAI Conferences

The majority of speech recognition systems today commonly use Hidden Markov Models (HMMs) as acoustic models in systems since they can powerfully train and map a speech utterance into a sequence of units. Such systems perform even better if the units are context-dependent. Analogously, when HMM techniques are applied to the problem of articulatory feature extraction, contextdependent articulatory features should definitely yield a better result. This paper shows a possible strategy to extend a typical HMM-based articulatory feature extraction system into a context-dependent version which exhibits higher accuracy.


Data Scientist - Machine Learning @ Booking.com

#artificialintelligence

Would you like to translate terabytes of data into unforgettable holidays for millions of people around the globe? Booking.com, the world's largest accommodation booking website, is looking for rock star Data Scientists to add to join our highly successful Personalization Team within the Front End department. This product development team crunches endless amounts of data to provide our customers with the best possible experience. They focus on anything from understanding and predicting market data, to ranking all properties on our website, and providing our customers with the most relevant personalized recommendations. As a Data Scientist you'll work side by side with Developers, Designers and Product Owners, and take full ownership of your work – from the initial idea-generation phase to the implementation of the final product on our website.


The 7 Best Data Science and Machine Learning Podcasts

@machinelearnbot

Data science and machine learning have long been interests of mine, but now that I'm working on Fuzzy.ai and trying to make AI and machine learning accessible to all developers, I need to keep on top of all the news in both fields. My preferred way to do this is through listening to podcasts. I've listened to a bunch of machine learning and data science podcasts in the last few months, so I thought I'd share my favorites: Every other week, they release a 10–15 minute episode where hosts, Kyle and Linda Polich give a short primer on topics like k-means clustering, natural language processing and decision tree learning, often using analogies related to their pet parrot, Yoshi. This is the only place where you'll learn about k-means clustering via placement of parrot droppings. Hosted by Katie Malone and Ben Jaffe of online education startup Udacity, this weekly podcast covers diverse topics in data science and machine learning: teaching specific concepts like Hidden Markov Models and how they apply to real-world problems and datasets.