Hands-on machine learning with Python : implement neural network solutions with Scikit-learn and PyTorch /

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Here is the perfect comprehensive guide for readers with basic to intermediate level knowledge of machine learning and deep learning. It introduces tools such as NumPy for numerical processing, Pandas for panel data analysis, Matplotlib for visualization, Scikit-learn for machine learning, and Pytor...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Pajankar, Ashwin (Autor), Joshi, Aditya (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: [Berkeley] : Apress, [2022]
Temas:
Machine learning.
Python (Computer program language)
Apprentissage automatique.
Python (Langage de programmation)
Machine learning
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)
Tabla de Contenidos:
  • Chapter 1: Getting Started with Python 3 and Jupyter Notebook
  • Chapter 2: Getting Started with NumPy
  • Chapter 3 : Introduction to Data Visualization
  • Chapter 4 : Introduction to Pandas
  • Chapter 5: Introduction to Machine Learning with Scikit-Learn
  • Chapter 6: Preparing Data for Machine Learning
  • Chapter 7: Supervised Learning Methods - 1
  • Chapter 8: Tuning Supervised Learners
  • Chapter 9: Supervised Learning Methods - 2
  • Chapter 10: Ensemble Learning Methods
  • Chapter 11: Unsupervised Learning Methods
  • Chapter 12: Neural Networks and Pytorch Basics
  • Chapter 13: Feedforward Neural Networks
  • Chapter 14: Convolutional Neural Network
  • Chapter 15: Recurrent Neural Network
  • Chapter 16: Bringing It All Together.

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