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Data Science Articles & Videos
Personalized Recommendations for Experiences Using Deep Learning
As the world’s largest travel site, TripAdvisor provides a platform for billions of users to research, book, and review their trips across the world. In this blog post, we will explain how our newly-developed ‘Recommended For You’ (RFY) model generates personalized recommendations on our website using users’ browsing history and deep learning. The model has already been tested in production and demonstrated lifts in user engagement and bookings...
Combining online and offline tests to improve News Feed ranking
A/B testing is an important part of the product improvement cycle for machine learning (ML) technologies. But applying advanced techniques such as Bayesian optimization to optimize these systems can be challenging due to resource limitations. We propose a new multitask Bayesian optimization approach that combines observations from online A/B tests with a simple offline simulator. This model allows for jointly optimizing up to 20 parameters with as few as 40 total online A/B tests...
Neural Machine Translation With Attention Mechanism
Hello guys, spring has come and I guess you’re all feeling good. Today, let’s join me in the journey of creating a neural machine translation model with attention mechanism by using the hottest-on-the-news Tensorflow 2.0...
Diagnosing and Enhancing VAE Models
Although variational autoencoders (VAEs) represent a widely influential deep generative model, many aspects of the underlying energy function remain poorly understood. In particular, it is commonly believed that Gaussian encoder/decoder assumptions reduce the effectiveness of VAEs in generating realistic samples. In this regard, we rigorously analyze the VAE objective, differentiating situations where this belief is and is not actually true. We then leverage the corresponding insights to develop a simple VAE enhancement that requires no additional hyperparameters or sensitive tuning...
Preparing your own ML training data?
It takes a lot of data to train an algorithm that is production-ready. For an algorithm to be highly accurate, you absolutely need ata that is labeled and annotated with nearly flawless quality. If you’re not sure what it takes to produce enormous volumes of quality training data, you need the Blueprint....
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Data Scientist (Analytics) - Pear Therapeutics - San Francisco or Boston
At Pear Therapeutics, we have the privilege of building the world’s first-ever class of prescription digital therapeutics. By nature of our therapeutics as digital applications, we have access to rich datasets and unique opportunities to drive clinical outcomes. As a Data Scientist, you will be responsible for shaping and delivering data-driven insights. We are looking for data scientists with a deep product sense, who have an innate curiosity, and are eager to dive into large, complex datasets and create actionable insights...
Training & Resources
Reproducible Research with R and R Studio
"a very practical book that teaches good practice in organizing reproducible data analysis and comes with a series of examples..."...
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