Lecture

Intraday Data Analysis

In course

Exercitation dolore in id pariatur cupidatat enim. Quis sit cillum voluptate nulla commodo esse. Veniam quis aute quis ea proident irure elit adipisicing nisi consectetur. Do sit ad elit eiusmod elit do nostrud in consequat eiusmod nisi. Voluptate exercitation occaecat pariatur qui mollit non magna cillum. Dolor amet qui in esse culpa. Lorem reprehenderit exercitation magna aliquip aliquip esse sit cillum occaecat fugiat et consectetur ad voluptate.

Description

This lecture focuses on analyzing intraday data, covering topics such as trade files, systematic studies, breakpoints in script languages, debugging techniques, and better programming practices. It also delves into multicore computing in Python, GPU programming, correlation computation with GPUs, and the use of libraries like Thrust and Numba for faster computations.

Instructor

Proident et laborum reprehenderit reprehenderit aliqua velit tempor qui nulla. Lorem culpa qui aliquip qui incididunt pariatur deserunt laboris aute anim occaecat do sint occaecat. Anim nulla ex excepteur in non eiusmod. Ullamco nulla non incididunt magna do sit ea pariatur fugiat consectetur cupidatat ea. Veniam minim duis cillum occaecat non dolore duis commodo mollit pariatur nostrud ex aute excepteur.

Official source

https://mediaspace.epfl.ch/media/0_un3nw77f

About this result

This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Ontological neighbourhood

Computer engineering

High-performance computing: Parallel computing

Related lectures (32)

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.