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Hands-on Machine Learning with Python

Implement Neural Network Solutions with Scikit-learn and PyTorch

Produktform: E-Buch Text Elektronisches Buch in proprietärem

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 Pytorch for deep learning with Python. It also serves as a long-term reference manual for the practitioners who will find solutions to commonly occurring scenarios.The book is divided into three sections. The first section introduces you to number crunching and data analysis tools using Python with in-depth explanation on environment configuration, data loading, numerical processing, data analysis, and visualizations. The second section covers machine learning basics and Scikit-learn library. It also explains supervised learning, unsupervised learning, implementation, and classification of regression algorithms, and ensemble learning methods in an easy manner with theoretical and practical lessons. The third section explains complex neural network architectures with details on internal working and implementation of convolutional neural networks. The final chapter contains a detailed end-to-end solution with neural networks in Pytorch.After completing , you will be able to implement machine learning and neural network solutions and extend them to your advantage.  Data scientists, machine learning engineers, and software professionals with basic skills in Python programming. weiterlesen

Elektronisches Format: PDF

Sprache(n): Englisch

ISBN: 978-1-4842-7921-2 / 978-1484279212 / 9781484279212

Verlag: APRESS

Erscheinungsdatum: 05.03.2022

Seiten: 335

Autor(en): Ashwin Pajankar, Aditya Joshi

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