Welcome into my Arctic Vault !
Mon idée ici est de regrouper tout ce qui peut m'être utile, et de formaliser mes pensées, sur le deep learning, le DevOps, le MLOps, etc.
Ressources générales
- The Matrix Calculus You Need For Deep Learning
- Statisticians say the darndest things
- Distill
- CS231n: Convolutional Neural Networks for Visual Recognition
- CS229: Machine Learning
- Stanford Welcome to the Deep Learning Tutorial!
- Mathematics for Machine Learning
- Neural Networks and Deep Learning
- Learn TensorFlow and deep learning, without a Ph.D.
- The Twelve-Factor App
- Yann Le Cun Deep Learning printemps 2020
- The Missing Semester of Your CS Education
- Great Practical Ideas in Computer Science
- Code. Simply. Clearly. Calmly.
- Gestion sémantique de version
- Use Bash Strict Mode (Unless You Love Debugging)
- Understanding the Fourier Transform by example
- ML Notebooks
- srsly: Modern high-performance serialization utilities for Python
- Radically efficient machine teaching. An annotation tool powered by active learning.
- A refreshing functional take on deep learning, compatible with your favorite libraries.
Rédaction documentation Python
Formating, Linting, Type Hinting
- flake8
- isort
- Black : The uncompromising code formatter
- mypy
- rope (refactoring)
- Static Code Analysis for Python
- Complexity Waterfall
- Jones complexity
- wemake-python-styleguide Best practices
Test unitaires
Intégration, développement continu
- Gestion des dépendances
- pre-commit
- Automate Python workflow using pre-commits: black and flake8
- Continuous Delivery for Machine Learning
- Continuous Delivery 101
- GoCD User Documentation
- GitHub Actions for perfect Python Continuous Integration
- Build Bot
- How to Add Domains
- How to Create, Edit, and Delete DNS Records
Docker
- Dockerize your Development Environment
- Developing inside a Container
- devcontainer.json reference
- Advanced Container Configuration
- Creating an API with FastAPI and Docker
- Faster Docker builds with pipenv, poetry, or pip-tools
- Publishing Docker images
- Awesome Docker Compose samples
Code quality
- Radon and code metrics
- Métriques d'Halstead
- Think Twice Before Using the “Maintainability Index”
- Using Metrics to Evaluate Software System Maintainabilitv
Code security
A trier
- How to set up a perfect Python project
- The Magical Number Seven, Plus or Minus Two
- Key Kubernetes Concepts
- GoCD User Documentation
- Starting New Python Project in VSCode
- Configuring Python Workspace: Poetry
- Vulture - Find dead code
packaging
FastAPI
Guidelines machine learning, MLOps : ressources
Deep Learning tips and tricks
- Encoding Cyclical Features for Deep Learning
- 2D Convolution as a Doubly Block Circulant Matrix Operating on a Vector
- Tuning the \(\varepsilon\) parameter
- Super-convergence in Tensorflow 2 with the 1Cycle Policy
- The Mathematical Engineering of Deep Learning
MLOps
- Awesome MLOps
- Full Stack Deep Learning
- A Guide to Terraform for Data Scientists
- From Training to Serving: Machine Learning Models with Terraform
- Manage Azure Machine Learning workspaces using Terraform
Data Versioning
- DVC
- Data Version Control With Python and DVC
- First Impressions of Data Science Version Control (DVC)
Monitoring
- Monitoring is a means, not an end
- MLOps: Model Monitoring 101
- Data Monitoring avec great_expectations
- Great expectations — An Introduction.
- TensorFlow Data Validation