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

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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Bibliographic Details
Main Authors: Pajankar, Ashwin, (Author), Joshi, Aditya, (Author)
Format: eBook
Language: English
Published: [Berkeley] : Apress, [2022]
Subjects:
Machine learning.
Python (Computer program language)
elektronické knihy
electronic books
ISBN: 9781484279212
1484279212
1484279204
9781484279205
Physical Description: 1 online resource : illustrations

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Table of contents

LEADER 04628cam a2200445 i 4500
001 kn-on1302584590
003 OCoLC
005 20240717213016.0
006 m o d
007 cr cn|||||||||
008 220309s2022 caua o 001 0 eng d
040 |a GW5XE  |b eng  |e rda  |e pn  |c GW5XE  |d ORMDA  |d YDX  |d OCLCO  |d EBLCP  |d OCLCO  |d OCLCF  |d N$T  |d TOH  |d UKAHL  |d OCLCQ  |d OCLCO  |d OCLCL  |d OCLCQ 
020 |a 9781484279212  |q (electronic bk.) 
020 |a 1484279212  |q (electronic bk.) 
020 |z 1484279204 
020 |z 9781484279205 
024 7 |a 10.1007/978-1-4842-7921-2  |2 doi 
024 8 |a 9781484279212 
035 |a (OCoLC)1302584590  |z (OCoLC)1302338986  |z (OCoLC)1302689683  |z (OCoLC)1302740725  |z (OCoLC)1302953704  |z (OCoLC)1302987087  |z (OCoLC)1303052573  |z (OCoLC)1303075657  |z (OCoLC)1303184233  |z (OCoLC)1303215149  |z (OCoLC)1303559077 
100 1 |a Pajankar, Ashwin,  |e author. 
245 1 0 |a Hands-on machine learning with Python :  |b implement neural network solutions with Scikit-learn and PyTorch /  |c Ashwin Pajankar, Aditya Joshi. 
264 1 |a [Berkeley] :  |b Apress,  |c [2022] 
264 4 |c ©2022 
300 |a 1 online resource :  |b illustrations 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
500 |a Includes index. 
506 |a Plný text je dostupný pouze z IP adres počítačů Univerzity Tomáše Bati ve Zlíně nebo vzdáleným přístupem pro zaměstnance a studenty 
520 |a 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 Hands-on Machine Learning with Python, you will be able to implement machine learning and neural network solutions and extend them to your advantage. You will: Review data structures in NumPy and Pandas Demonstrate machine learning techniques and algorithm Understand supervised learning and unsupervised learning Examine convolutional neural networks and Recurrent neural networks Get acquainted with scikit-learn and PyTorch Predict sequences in recurrent neural networks and long short term memory . 
505 0 |a 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. 
504 |a Includes bibliographical references and index. 
590 |a Knovel  |b Knovel (All titles) 
650 0 |a Machine learning. 
650 0 |a Python (Computer program language) 
655 7 |a elektronické knihy  |7 fd186907  |2 czenas 
655 9 |a electronic books  |2 eczenas 
700 1 |a Joshi, Aditya,  |e author. 
776 0 8 |i Print version:  |a PAJANKAR, ASHWIN. JOSHI, ADITYA.  |t HANDS-ON MACHINE LEARNING WITH PYTHON.  |d [Place of publication not identified] : APRESS, 2022  |z 1484279204  |w (OCoLC)1274198520 
856 4 0 |u https://proxy.k.utb.cz/login?url=https://app.knovel.com/hotlink/toc/id:kpHMLPINN2/hands-on-machine?kpromoter=marc  |y Full text 

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