Deep Learning for Natural Language Processing: Creating Neural Networks with Python
By 作者: Palash Goyal - Sumit Pandey - Karan Jain
ISBN-10 书号: 148423684X
ISBN-13 书号: 9781484236840
Edition 版本: 1st ed.
Release Finelybook 出版日期: 2018-08-22
Pages 页数: 277
The Book Description robot was collected from Amazon and arranged by Finelybook
Discover the concepts of deep learning used for natural language processing (NLP), with full-fledged examples of neural network models such as recurrent neural networks, long short-term memory networks, and sequence-2-sequence models.
You’ll start by covering the mathematical prerequisites and the fundamentals of deep learning and NLP with practical examples. The first three chapters of the book cover the basics of NLP, starting with word-vector representation before moving onto advanced algorithms. The final chapters focus entirely on implementation, and deal with sophisticated architectures such as RNN, LSTM, and Seq2seq, using Python tools: TensorFlow, and Keras. Deep Learning for Natural Language Processing follows a progressive approach and combines all the knowledge you have gained to build a question-answer chatbot system.
This book is a good starting point for people who want to get started in deep learning for NLP. All the code presented in the book will be available in the form of IPython notebooks and scripts, which allow you to try out the examples and extend them in interesting ways.
What You Will Learn
Gain the fundamentals of deep learning and its mathematical prerequisites
Discover deep learning frameworks in Python
Develop a chatbot
Implement a research paper on sentiment classification
Who This Book Is For
Software developers who are curious to try out deep learning with NLP.
1.Introduction to Natural Language Processing and Deep Learning
2.Word Vector Representations
3.Unfolding Recurrent Neural Networks
4.Developing a Chatbot
5.Research Paper Implementation:Sentiment Classification
未经允许不得转载：finelybook » Deep Learning for Natural Language Processing: Creating Neural Networks with Python
- Python Machine Learning Workbook for Beginners: 10 Machine Learning Projects Explained from Scratch
- MCA Microsoft Office Specialist (Office 365 and Office 2019) Study Guide: Excel Associate Exam MO-200
- Practical Process Automation: Orchestration and Integration in Microservices and Cloud Native Architectures
- Practical Deep Learning: A Python-Based Introduction
- MCA Microsoft Office Specialist (Office 365 and Office 2019) Study Guide: Word Associate Exam MO-100
- Improving the Quality of ABAP Code: Striving for Perfection
- Frontiers in Quantum Computing
- Data Governance: The Definitive Guide: People, Processes, and Tools to Operationalize Data Trustworthiness