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The technical tagteam behind this blog. We aim to showcase the latest research, tools, and hardware for developing AI applications.

TF-Recommenders & Kubernetes for flexible RecSys Model Development & Deployment

Introducing TF-Recommenders Recently, Google open sourced a Keras API for building recommender systems called TF-Recommenders. TF-Recommenders is flexible, making it easy to integrate heterogeneous signals like implicit ratings from user interactions, content embeddings, or real-time context info. This module also introduces losses specialized for ranking and retrieval which can be combined to benefit from multi-task learning. The developers emphasize the ease-of-use in research, as well as the robustness for deployment in web-scale applications....

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TF-Ranking and BERT for Movie Recommendations

Check out our repo for all the code referenced in this blog! Recommender systems are used by many groups to maximize the presentation of products to users. There is a variety of implementations for building recommender systems, but at their core, these systems are designed to sort a universe of items by their relevance to a user based on user information, item information, or both. One well known algorithm for solving the sorting problem is the Learn-to-Rank model, where the objective is to rank a list of examples by each item鈥檚 relevance to a particular user....

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IVA Pipelines with NVIDIA TLT and Deepstream SDK 5.0

We have seen applications in industries like retail, telemedicine, and robotics enabled by video analytics with machine learning. ML practitioners often leverage transfer learning with pretrained models to expedite development. Computer vision applications can benefit from using video analytics frameworks to facilitate faster iteration and experimentation. NVIDIA鈥檚 TLT toolkit and the Deepstream SDK 5.0 have made it easy to experiment with various network architectures and quickly deploy them on a NVIDIA powered device for optimized inference....

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Population Health Modeling

In a matter of months, the COVID-19 pandemic has besieged humanity and now the world wrestles to manage the population health challenges of a novel coronavirus with remarkable infectivity. Organizing an effective response to blunt the impact of such a large, complex challenge demands a principled and scientific approach. Better Planning by Forecasting Infections Reliable forecasting is crucial for planning and allocating limited resources efficiently and minimizing casualties. A most important characteristic of an infective virus is its average rate of reproduction or $R_0$....

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Deepfake Detection: Challenge Accepted

Advances in methods to generate photorealistic but synthetic images have prompted concerns about abusing the technology to spread misinformation. In response, major tech companies like Facebook, Amazon, and Microsoft partnered to sponsor a contest hosted by Kaggle to mobilize machine learning talent to tackle the challenge. With $1 million in prizes and nearly half a terabyte of samples to train on, this contest requires the development of models that can be deployed to combat deepfakes....

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