Passer au contenu
Récents :
  • GitHub – jalammar/ecco: Visualize and explore NLP language models. Ecco creates interactive visualizations directly in Jupyter notebooks explaining the behavior of Transformer-based language models (like GPT2).
  • Data Science Infographic
  • SIRUS: Stable and Interpretable RUle Set
  • CLIP: Connecting Text and Images
  • Build Your own Recommendation Engine-Netflix Demystified: Demo+Code

Notes de Francis

  • Accueil
    • Notes
    • Uncategorized
  • Machine Learning
    • Deep Learning
    • NLP
    • GPU
    • Google AI
  • DevOps
    • Azure
    • Container
  • Code
    • Python
    • GitHub
    • Raspberry Pi
  • Design
    • Visual
  • Startup
    • Human Resources
  • Social Media
  • SEO
Notes 

Linear Algebra and Probability Theory Review for ML

12 novembre 2019 Francis

https://towardsdatascience.com/linear-algebra-and-probability-theory-review-for-ml-e3d2d70c5eb3

Linear Algebra and Probability Theory Review for ML
Probability theory is our way of dealing with uncertainty in the world, It’s the mathematical framework that estimates the probability of an event happening with respect to other possible events…
towardsdatascience.com

Partager :

  • Cliquez pour partager sur Twitter(ouvre dans une nouvelle fenêtre)
  • Cliquez pour partager sur Facebook(ouvre dans une nouvelle fenêtre)

Articles similaires

  • ← GPT2 Pretrained Models (Pytorch) | Kaggle
  • Pretrained Model Weights (Pytorch) | Kaggle →

Vous pourrez aussi aimer

Generative Model with Dynamic Linear Flow

9 mai 2019 Francis

2010.10442 BERT2DNN: BERT Distillation with Massive Unlabeled Data for Online E-Commerce Search

21 octobre 2020 Francis

Topic Modeling with Gensim

18 août 2020 Francis
Copyright © 2021 Notes de Francis. Tous droits réservés.
Theme ColorMag par ThemeGrill. Propulsé par WordPress.