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{ "item_title" : "Hands-On Machine Learning with Python", "item_author" : [" Ashwin Pajankar", "Aditya Joshi "], "item_description" : "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-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. What You'll LearnReview data structures in NumPy and Pandas Demonstrate machine learning techniques and algorithmUnderstand supervised learning and unsupervised learning Examine convolutional neural networks and Recurrent neural networksGet acquainted with scikit-learn and PyTorchPredict sequences in recurrent neural networks and long short term memory Who This Book Is ForData scientists, machine learning engineers, and software professionals with basic skills in Python programming.", "item_img_path" : "https://covers2.booksamillion.com/covers/bam/1/48/427/920/1484279204_b.jpg", "price_data" : { "retail_price" : "64.99", "online_price" : "64.99", "our_price" : "64.99", "club_price" : "64.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Hands-On Machine Learning with Python|Ashwin Pajankar

Hands-On Machine Learning with Python : Implement Neural Network Solutions with Scikit-Learn and Pytorch

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Overview

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-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.
What You'll Learn

  • 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

Who This Book Is For
Data scientists, machine learning engineers, and software professionals with basic skills in Python programming.

Details

  • ISBN-13: 9781484279205
  • ISBN-10: 1484279204
  • Publisher: Apress
  • Publish Date: March 2022
  • Dimensions: 10 x 7 x 0.74 inches
  • Shipping Weight: 1.36 pounds
  • Page Count: 335

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