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20182.mldl's Introduction

Una introducción a las técnicas de Machine Learning y Deep Learning

Materiales, Notebooks, Talleres y Soluciones

Videos

Sesión 1: Modelos derivados de los datos. Intro a Python/Numpy/Pandas

Parte 1
 Parte 2

Sesión 2: Diseño de algoritmos ML. Aprendizaje supervisado. Métodos de ensemble. Flujo de trabajo ML

Parte 1
 Parte 2

Sesión 4: Aprendizaje no supervisado. Reducción de la dimensionalidad. Aprendiendo representaciones

Parte 1
 Parte 2

Sesión 4: Introducción a las redes neuronales y a TensorFlow

Parte 1
 Parte 2

Sesión 5: Analtica de imágenes con redes convolucionales. Transfer Learning

Parte 1
 Parte 2

Sesión 6: Analtica de series temporales. Redes Recurrentes

Parte 1

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Recommended readings

  • Hastie, Tibshirani, Friedman, The Elements of Statistical Learning, Springer-Verlag website (with download)
  • Goodfellow, Bengio, Courville, Deep Learning, MIT Press website (with download)

Suggested Challenges

20182.mldl's People

Contributors

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