My Account Log in

1 option

Natural Language Processing Projects : Build Next-Generation NLP Applications Using AI Techniques / by Akshay Kulkarni, Adarsha Shivananda, Anoosh Kulkarni.

O'Reilly Online Learning: Academic/Public Library Edition Available online

View online
Format:
Book
Author/Creator:
Kulkarni, Akshay, author.
Shivananda, Adarsha, author.
Kulkarni, Anoosh, author.
Language:
English
Subjects (All):
Artificial intelligence.
Machine learning.
Python (Computer program language).
Artificial Intelligence.
Machine Learning.
Python.
Local Subjects:
Artificial Intelligence.
Machine Learning.
Python.
Physical Description:
1 online resource (327 pages)
Edition:
1st ed. 2022.
Place of Publication:
Berkeley, CA : Apress : Imprint: Apress, 2022.
Summary:
Leverage machine learning and deep learning techniques to build fully-fledged natural language processing (NLP) projects. Projects throughout this book grow in complexity and showcase methodologies, optimizing tips, and tricks to solve various business problems. You will use modern Python libraries and algorithms to build end-to-end NLP projects. The book starts with an overview of natural language processing (NLP) and artificial intelligence to provide a quick refresher on algorithms. Next, it covers end-to-end NLP projects beginning with traditional algorithms and projects such as customer review sentiment and emotion detection, topic modeling, and document clustering. From there, it delves into e-commerce related projects such as product categorization using the description of the product, a search engine to retrieve the relevant content, and a content-based recommendation system to enhance user experience. Moving forward, it explains how to build systems to find similar sentences using contextual embedding, summarizing huge documents using recurrent neural networks (RNN), automatic word suggestion using long short-term memory networks (LSTM), and how to build a chatbot using transfer learning. It concludes with an exploration of next-generation AI and algorithms in the research space. By the end of this book, you will have the knowledge needed to solve various business problems using NLP techniques. You will: Implement full-fledged intelligent NLP applications with Python Translate real-world business problem on text data with NLP techniques Leverage machine learning and deep learning techniques to perform smart language processing Gain hands-on experience implementing end-to-end search engine information retrieval, text summarization, chatbots, text generation, document clustering and product classification, and more.
Contents:
Chapter 1: Natural Language Processing and Artificial Intelligence Overview
Chapter 2: Product360 - Sentiment and Emotion Detector
Chapter 3: TED Talks Segmentation and Topics Extraction Using Machine Learning
Chapter 4: Enhancing E-commerce Using an Advanced Search Engine and Recommendation System
Chapter 5: Creating a Resume Parsing, Screening, and Shortlisting System
Chapter 6: Creating an E-commerce Product Categorization Model Using Deep Learning
Chapter 7: Predicting Duplicate Questions in Quora
Chapter 8: Named Entity Recognition Using CRF and BERT
Chapter 9: Building a Chatbot Using Transfer Learning
Chapter 10: News Headline Summarization
Chapter 11: Text Generation - Next Word Prediction
Chapter 12: Conclusion and Future Trends. .
Notes:
Includes index.
ISBN:
9781484273869
1484273869
OCLC:
1287894989
Publisher Number:
9781484273852
9781484273869

The Penn Libraries is committed to describing library materials using current, accurate, and responsible language. If you discover outdated or inaccurate language, please fill out this feedback form to report it and suggest alternative language.

Find

Home Release notes

My Account

Shelf Request an item Bookmarks Fines and fees Settings

Guides

Using the Find catalog Using Articles+ Using your account