#HUYEN CHIP BLOG ESSAY GRADER PROJECT365 FULL#

Spotlight talk at Prioritising Online Content workshop, NIPS 2017. The Propagation of Lies: Impeding the Spread of Misinformationĭetect echo chambers and recommend content of different perspectives. Oleksii Kuchaiev, Jason Li, Huyen Nguyen, Oleksii Hrinchuk, Ryan Leary, Boris Ginsburg, Samuel Kriman, Stanislav Beliaev, Vitaly Lavrukhin, Jack Cook, Patrice Castonguay, Mariya Popova, Jocelyn Huang, Jonathan M CohenĪccepted to Machine Learning Systems workshop at NeurIPS 2019. NeMo: a toolkit for building AI applications using Neural Modules

#HUYEN CHIP BLOG ESSAY GRADER PROJECT365 FULL#

My research focuses on the intersection between Natural Language Processing and Deep Learning.įor the full list of papers, see my Google Scholar profile. I occasionally write papers and/or support my coworkers with their papers. Spotlight talk at NIPS Workshop on Prioritising Online Content (Long Beach, USA)Īug 5, 2012: Traveling is an equal opportunity Guest lecture for Stanford’s CS224N class (Stanford, USA)ĭec 9, 2017: Mitigating the spread of fake news by identifying and disrupting echo chambers Sep 12, 2019: State-of-the-art Machine Translation VietAI Summit (Ho Chi Minh City, Vietnam) Nov 2, 2019: Machine Learning Interivews (talk) | AI In Industry and Vietnam (panel) Nov 16-17, 2019: Machine Learning Interviews Jul 22, 2020: Machine Learning Production PipelineĬhallenges in Deploying and Monitoring Machine Learning Systems ICML (Vienna, Austria)ĭec 9, 2019: Panel on research vs production Nov 12, 2020: Machine learning production mythsĪug 20, 2020: Machine Learning Production Nov 18, 2020: Machine learning production Nov 19, 2020: Machine learning production Jan 20, 2021: Machine learning is going real-time Please don’t expect me to promote your event if I agree to speak. I feel very awkward when an organizer asks me to do so. I avoid posting promotional content (e.g. Below is the selected list of my talks ( not updated). deep learning fundamentals, applications, and trends.community building and developer relations.machine learning interviews and recruiting pipeline.machine learning in production at scale.real-time machine learning: online prediction, real-time model analytics, continual learning.The data and charts on the following pages is a compilation of the past year.I’m grateful for every opportunity to share my work. After collecting the data for a few months I decided I would collect the data for one full year and make a year end report. I continued to log my time after the first month because I did not want to miss any important event that might happen and change the results. I was hoping I would look at the results and it would be obvious that I watch too much television, or spend too much time with friends, or I spend too much time at the bar.Īt the beginning, I did not set a deadline to complete the research I guess I had in the back of my head that it would last a couple weeks or maybe a month. I always tell myself there are not enough hours in a day and I do not have enough time to complete projects. When I first started the project it was intended to help me find more time to work on projects. I have been logging hours spent on each activity I do throughout each day. Since October 2013 I have been working on a personal project about how I spend my time.

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