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

Show other versions (1)

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...

Full description

Bibliographic Details
Call Number:Libro Electrónico
Main Authors: Pajankar, Ashwin (Author), Joshi, Aditya (Author)
Format: Electronic eBook
Language:Inglés
Published: [Berkeley] : Apress, [2022]
Subjects:
Machine learning.
Python (Computer program language)
Apprentissage automatique.
Python (Langage de programmation)
Machine learning
Online Access:Texto completo (Requiere registro previo con correo institucional)
Table of Contents:
  • 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.

Similar Items