English Version
館藏查詢
他校館藏
  
   系統號碼840936
   書刊名Codeless deep learning with KNIME : build, train, and deploy various deep neural network architectures using KNIME Analytics Platform /
   主要著者Melcher, Kathrin, author
   其他著者Silipo, Rosaria,
   出版項Mumbai : Packt, 2020
   索書號QA76.9.D343.M45 2020
   ISBN9781800566613
   標題Data mining.
Machine learning.
Natural language processing (Computer science)
Data mining.-fast-(OCoLC)fst00887946
Machine learning.-fast-(OCoLC)fst01004795
Natural language processing (Computer science)-fast-(OCoLC)fst01034365
   
    
   分享▼ 
網站搜尋           

 資料類型狀態應還日期預約人數館藏地索書號條碼號
教學專用借出中2024/08/280總館
西文圖書區
QA76.9.D343 .M45 2020W114175
找書圖書在架上0總館
西文圖書區 Shelf
QA76.9.D343 .M45 2020W114905

內容簡介"KNIME Analytics Platform is an open source software used to create and design data science workflows. This book is a comprehensive guide to the KNIME GUI and KNIME deep learning integration, helping you build neural network models without writing any code. It’ll guide you in building simple and complex neural networks through practical and creative solutions for solving real-world data problems. Starting with an introduction to KNIME Analytics Platform, you’ll get an overview of simple feed-forward networks for solving simple classification problems on relatively small datasets. You’ll then move on to build, train, test, and deploy more complex networks, such as autoencoders, recurrent neural networks (RNNs), long short-term memory (LSTM), and convolutional neural networks (CNNs). In each chapter, depending on the network and use case, you’ll learn how to prepare data, encode incoming data, and apply best practices. By the end of this book, you’ll have learned how to design a variety of different neural architectures and will be able to train, test, and deploy the final network"--Back cover

讀者書評

尚無書評,

相關借閱1.Data visualization with Python and JavaScript : scrape, clean, explore & transform your data /
2.Advanced forecasting with Python with state-of-the-art-models including LSTMs, Facebook's Prophet, and Amazon's DeepAR
3.Deep learning with PyTorch 1.x : implement deep learning techniques and neural network architecture variants using Python /
4.Programming PyTorch for deep learning : creating and deploying deep learning applications /
5.Pytorch deep learning by example (2nd Edition): grasp deep learning from scratch like AlphaGo Zero within 40 days
6.The deep learning with PyTorch workshop. build deep neural networks and artificial intelligence applications with PyTorch /
7.Deep learning for coders with fastai and PyTorch : AI applications without a PhD /
8.Applied text analysis with Python : enabling language-aware data products with machine learning /
9.Blockchain with Hyperledger Fabric : build decentralized applications using Hyperledger Fabric 2 /
10.Blockchain for business with hyperledger fabric: a complete guide to enterprise blockchain implementation using Hyperledger Fabric.

  
Copyright © 2007 元智大學(Yuan Ze University) ‧ 桃園縣中壢市 320 遠東路135號 ‧ (03)4638800