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Solving for Productivity in Data Science with Modin and AI Optimizations
저장한 시리즈 ("피드 비활성화" status)
When? This feed was archived on September 08, 2022 20:29 (). Last successful fetch was on August 08, 2022 23:26 ()
Why? 피드 비활성화 status. 잠시 서버에 문제가 발생해 팟캐스트를 불러오지 못합니다.
What now? You might be able to find a more up-to-date version using the search function. This series will no longer be checked for updates. If you believe this to be in error, please check if the publisher's feed link below is valid and contact support to request the feed be restored or if you have any other concerns about this.
Manage episode 325176521 series 29991
The rapid advancement in machine learning and data science fields have aided data scientists in arriving at meaningful insights. However, it’s not been an easy task to optimize machine learning infrastructures to allow data scientists to focus on their core expertise. Today, we will discuss how certain tools and hardware optimizations are not only saving time, but also enabling data scientists to be more productive.
Learn more:
Ponder.io
Intel oneAPI AI Analytics Toolkit
Intel Distribution for Python
Intel Distribution of Modin
Intel Extension for Scikit-learn
Intel Optimization for PyTorch
Intel Optimization for TensorFlow
Guests:
Devin Petersohn, Cofounder and CTO of Ponder
Areg Melik-Adamyan, Principal Engineer and Engineering Manager at Intel
98 에피소드
저장한 시리즈 ("피드 비활성화" status)
When? This feed was archived on September 08, 2022 20:29 (). Last successful fetch was on August 08, 2022 23:26 ()
Why? 피드 비활성화 status. 잠시 서버에 문제가 발생해 팟캐스트를 불러오지 못합니다.
What now? You might be able to find a more up-to-date version using the search function. This series will no longer be checked for updates. If you believe this to be in error, please check if the publisher's feed link below is valid and contact support to request the feed be restored or if you have any other concerns about this.
Manage episode 325176521 series 29991
The rapid advancement in machine learning and data science fields have aided data scientists in arriving at meaningful insights. However, it’s not been an easy task to optimize machine learning infrastructures to allow data scientists to focus on their core expertise. Today, we will discuss how certain tools and hardware optimizations are not only saving time, but also enabling data scientists to be more productive.
Learn more:
Ponder.io
Intel oneAPI AI Analytics Toolkit
Intel Distribution for Python
Intel Distribution of Modin
Intel Extension for Scikit-learn
Intel Optimization for PyTorch
Intel Optimization for TensorFlow
Guests:
Devin Petersohn, Cofounder and CTO of Ponder
Areg Melik-Adamyan, Principal Engineer and Engineering Manager at Intel
98 에피소드
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