• Posts
My path to machine learning
Books
• Personal reading List
• Deep work
Machine Learning
• KL Divergence
• Variational Inference
Python
• Mocking
• Magical Universe
  • Start
  • The Tales of Castle Kilmere
  • Object-oriented programming
  • Types of methods
  • Type annotations
  • To-string conversion
  • Decorators
  • Properties
  • Underscore patterns
  • Extending the universe
  • Duck Typing
  • Namedtuples
  • Abstract Base Classes
  • Data classes
  • Immutable data classes
  • Decorators in classes
  • if __name__ == "__main__"
  • Context managers
  • Testing with pytest
  • Iterators
  • Multisets
  • Extending the universe II
  • Exception classes
  • functools.wraps
  • Defaultdict
  • Config files
  • Wrap up
Software Engineering
• Intro to containers
• Intro to Docker
• Intro to virtual machines

Personal reading list of non-fiction books

Books I am currently reading A Promised Land by Barack Obama Link to book Books I have read The Alchemy of Air by Thomas Hager (Link to book) Superintelligence: Paths, Dangers, Strategies by Nick Bostrom (Link to book) Beethoven, A Life by Jan Caeyers (Link to book) Deep Work: Rules for Focused Success in a Distracted World by Cal Newport (Link to book)

February 14, 2021 Read

Deep Work

I recently finished reading the book Deep Work by Cal Newport. For years, I have been interested in the question of how we can improve our learning and work habits. There is a ton of research on this topic and many great resources (like, for example, the podcast The Learning Scientists). I don’t want to use this blog post to talk about all the different things I have learned and tried in the past years.

December 18, 2020 Read