书目名称 | Hands-on Machine Learning with Python | 副标题 | Implement Neural Net | 编辑 | Ashwin Pajankar,Aditya Joshi | 视频video | | 概述 | Explains machine learning process through validation, evaluation, hyperparameter tuning and regularization.Discusses neural network architectures for predicting sequences in the form of Recurrent Neur | 图书封面 |  | 描述 | 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 theoreticaland 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-en | 出版日期 | Book 2022 | 关键词 | Machine Learning; Python; Data Science; Numpy; Pandas; Matplotlib; CNN; RNN; LSTM; Keras; TensorFlow; PyTorch | 版次 | 1 | doi | https://doi.org/10.1007/978-1-4842-7921-2 | isbn_softcover | 978-1-4842-7920-5 | isbn_ebook | 978-1-4842-7921-2 | copyright | Ashwin Pajankar and Aditya Joshi 2022 |
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