Aaron Richter- Parallel Processing in Python| PyData Global 2020
Talk
Python has a vast ecosystem of tools for scientific computing and data science. However, when data size or computational complexity grows, users may encounter performance challenges. This talk will cover the current landscape of parallel processing tools in Python, with a focus on which tools are best suited for various workloads such as arrays, dataframes, machine learning, and deep learning.
Speaker
Aaron Richter is a software developer turned data engineer and data scientist. He has pioneered the development and implementation of large-scale data science infrastructure in both business and research environments. Inevitably, he spent a lot of time finding efficient ways to clean data, run pipelines, and tune models. Aaron is a Senior Data Scientist at Saturn Cloud, and holds a PhD in machine learning from Florida Atlantic University.
www.pydata.org
PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.
PyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.
Видео Aaron Richter- Parallel Processing in Python| PyData Global 2020 канала PyData
Python has a vast ecosystem of tools for scientific computing and data science. However, when data size or computational complexity grows, users may encounter performance challenges. This talk will cover the current landscape of parallel processing tools in Python, with a focus on which tools are best suited for various workloads such as arrays, dataframes, machine learning, and deep learning.
Speaker
Aaron Richter is a software developer turned data engineer and data scientist. He has pioneered the development and implementation of large-scale data science infrastructure in both business and research environments. Inevitably, he spent a lot of time finding efficient ways to clean data, run pipelines, and tune models. Aaron is a Senior Data Scientist at Saturn Cloud, and holds a PhD in machine learning from Florida Atlantic University.
www.pydata.org
PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.
PyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.
Видео Aaron Richter- Parallel Processing in Python| PyData Global 2020 канала PyData
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