Lecture

Introduction to Data Science

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In course

ENG-209: Data science for engineers with Python

Ce cours propose une immersion progressive et complète dans le domaine de la Data Science à travers le langage Python. Il guide les étudiants depuis la manipulation de données brutes jusqu'à la modélisation et l'extraction de connaissances utiles à partir ...

Description

This lecture covers the fundamentals of data science, including the process of transforming raw data into valuable information. Topics include classification by decision trees, recent advances in machine learning with convolutional neural networks, and the application of deep reinforcement learning in AlphaGo Zero. The lecture also delves into the challenges of big data, the importance of refining data, and the transition from machine learning to data science. Practical examples and hands-on exercises are used to illustrate key concepts.

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Instructors (2)

Olivier Verscheure

SWISS DATA SCIENCE CENTER Housed at both EPFL and ETH Zurich, the newly created Swiss Data Science Center (SDSC) will address the fragmentation within today's data and analytics landscapes. The SDSC will be composed of a distributed multi-disciplinary team of data scientists and experts in domains including personalized health and personalized medicine, transportation, earth and environmental science, social science and digital humanities, and economics. The center aims to federate data providers, data and

Jean-Philippe Pellet

Teaching & PhD Courses Data science for engineers with Python ENG-209 This course offers a gradual and comprehensive introduction to the field of Data Science through the Python programming language. It guides students from raw data manipulation to modeling and the extraction of meaningful insights from real-world data.

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Related concepts (32)

Haiku

Haiku is a type of short form poetry that originated in Japan. Traditional Japanese haiku consist of three phrases composed of 17 phonetic units (called on in Japanese, which are similar to syllables) in a 5, 7, 5 pattern; that include a kireji, or "cutting word"; and a kigo, or seasonal reference. Similar poems that do not adhere to these rules are generally classified as senryū. Haiku originated as an opening part of a larger Japanese poem called renga.

Computer file

In computing, a computer file is a resource for recording data on a computer storage device, primarily identified by its . Just as words can be written on paper, so can data be written to a computer file. Files can be shared with and transferred between computers and mobile devices via removable media, networks, or the Internet. Different are designed for different purposes. A file may be designed to store an , a written message, a video, a program, or any wide variety of other kinds of data.

WxPython

wxPython is a wrapper for the cross-platform GUI API (often referred to as a "toolkit") wxWidgets (which is written in C++) for the Python programming language. It is one of the alternatives to Tkinter. It is implemented as a Python extension module (native code). In 1995, Robin Dunn needed a GUI application to be deployed on HP-UX systems but also run Windows 3.1 within short time frame. He needed a cross-platform solution. While evaluating free and commercial solutions, he ran across Python bindings on the wxWidgets toolkit webpage (known as wxWindows at the time).

Renku

, or haikai no renga, is a Japanese form of popular collaborative linked verse poetry. It is a development of the older Japanese poetic tradition of ushin renga, or orthodox collaborative linked verse. At renku gatherings participating poets take turns providing alternating verses of 17 and 14 morae. Initially haikai no renga distinguished itself through vulgarity and coarseness of wit, before growing into a legitimate artistic tradition, and eventually giving birth to the haiku form of Japanese poetry.

Entropy (information theory)

In information theory, the entropy of a random variable is the average level of "information", "surprise", or "uncertainty" inherent to the variable's possible outcomes. Given a discrete random variable , which takes values in the alphabet and is distributed according to : where denotes the sum over the variable's possible values. The choice of base for , the logarithm, varies for different applications. Base 2 gives the unit of bits (or "shannons"), while base e gives "natural units" nat, and base 10 gives units of "dits", "bans", or "hartleys".

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