This workshop series will present an extensive discussion on how to improve the performance of Python in data science by looking under the hood of its language/libraries and using the technologies to make Python a practical solution for the high-performance big data analytics. In the second session, we will focus on how to load/process the super big dataset in Python using a single machine and comparing the dataframe implementations from Pandas, Modin, Pandarallel, Dask and Vaex etc. Although no specific prerequisite is required to attend the talk, having programming experience in Python’s numpy and Pandas packages will be helpful to fully understand the lecture content.
data science
High-Performance Data Science in Python (1) Interpreter War
This workshop series will present an extensive discussion on how to improve the performance of Python in data science by looking under the hood of its language/libraries and using the technologies to make Python a practical solution for the high-performance big data analytics. In the first session, we will focus on how to boost the speed of python code in an interperter level by explaining the concepts (e.g. GIL, GIT) and introducing the packages of pypy, numba, pythran, cython etc. Although no specific prerequisite is required to attend the talk, having programming experience in Python will be helpful to fully understand the lecture content.
Early Career Research Project Site Launch
New space for early UCLA researchers to highlight their projects.
Introduction to Data Science with Python Part 2
The term “data science” has become a ubiquitous and all-encompassing term to address any field that utilizes data analytics in one form or another. Despite having such a broad mandate, certain elements remain consistent in the approach to data science that are interdisciplinary: data acquisition, data exploration, data modeling, and data communication. In this two-part…
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Introduction to Data Science with Python Part 1
The term “data science” has become a ubiquitous and all-encompassing term to address any field that utilizes data analytics in one form or another. Despite having such a broad mandate, certain elements remain consistent in the approach to data science that are interdisciplinary: data acquisition, data exploration, data modeling, and data communication. In this two-part…
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IDRE Early Career Research Day
Venue: Sequoia Room, UCLA Faculty Center, 480 Charles E. Young Drive East, Los Angeles Registration: RSVP link Contact: T.V.Singh The Institute for Digital Research and Education (IDRE) is pleased to announce the upcoming IDRE Early Career Research Day. This event is aimed to highlight the diverse research activities in computational science, data science, information science,…
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