Sébastien Pittet

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Technology enthusiast, Casual developer, ICT Professional working at Swisscom

Spéléologue, membre du Spéléo-Secours Suisse.

dimanche, 9 février 2020

Visiteurs

IMG_0600

mardi, 28 janvier 2020

Micro Trottoir 1963 Speleologie

Merci RTS Archives (et Pony  Express) !

Micro Trottoir de 1963, au sujet de la Spéléologie.

Quelques liens

mardi, 21 janvier 2020

Bivouac souterrain

Durant le week-end du 31 août - 1er septembre 2019, 13 secouristes du Spéléo-Secours (colonne 3) ont participé à un exercice au Gouffre de la Pleine Lune, une grotte qui cache l’une des plus grandes salles souterraines du jura vaudois. L’objectif de cette opération était d’entraîner les secouristes au séjour prolongé sous terre. Retour sur cet exercice.

lundi, 20 janvier 2020

Distance et ultrasons

A customer of mine asked the company about a project related to 'Internet of Things'. I just built this sensor, able to measure the distance (based on ultrasound transmitter).

All components come from the 'Inventor's kit 4.0' produced by Sparkfun. A newest version is now available and comes with the Redboard Qwiic, that allows you to connect a couple of breakboards in a row, with easy cabling. A must have if you want to learn eletronics from scratch.

https://www.sparkfun.com/products/15267

Capteur de distance à Ultrasons, janv. 2020

 

 

lundi, 6 janvier 2020

Foundations of Data Science

EPFL Extension School Logo, janv. 2020

After a couple of months of learning at EPFL Extension School, I finally got the diploma !

And I strongly recomment the Extension School : this was a great experience and I was nicely surprised by the quality of this course.

Each chapter contains a part of theory, followed by small exercices. At the end of the training, there is a big practical part, with projects to deliver.

The team of professors are available for discussions and more explanations. Very cool !

Thanks Swisscom for having paid this training !

Some Links

Content of the course

  1. Introduction
  2. Tables of data
  3. First steps with R
  4. Introduction to Datawrangling
  5. Literate programming
  6. Advanced Datawrangling
  7. Databases
  8. More Datawrangling
  9. Nested data and APIs
  10. HTML and Scraping
  11. Visualisation
  12. Analysis
  13. Machine Learning
  14. Media Data
  15. Data privacy and security
  16. Data and society
  17. Projects (6 R Notebooks to be created)

 

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