Sentiment Analysis

Sentiment Analysis with NLP using Python and Flask  eBooks & eLearning

Posted by lucky_aut at Jan. 4, 2021
Sentiment Analysis with NLP using Python and Flask

Sentiment Analysis with NLP using Python and Flask
Duration: 1h 25m | .MP4 1280x720, 30 fps(r) | AAC, 44100 Hz, 2ch | 459 MB
Genre: eLearning | Language: English

Along with a Project

Sentiment Analysis for PTSD Signals  eBooks & eLearning

Posted by ChrisRedfield at Dec. 13, 2015
Sentiment Analysis for PTSD Signals

Demetrios Sapounas - Sentiment Analysis for PTSD Signals
Published: 2013-11-11 | ISBN: 1461430968 | PDF | 81 pages | 1.3 MB

A Practical Guide to Sentiment Analysis (Socio-Affective Computing) [Repost]  eBooks & eLearning

Posted by Free butterfly at Nov. 12, 2019
A Practical Guide to Sentiment Analysis (Socio-Affective Computing) [Repost]

A Practical Guide to Sentiment Analysis (Socio-Affective Computing) by Erik Cambria, Dipankar Das, Sivaji Bandyopadhyay
English | April 12, 2017 | ISBN: 3319553925 | 196 pages | PDF | 2.49 Mb

A Practical Guide to Sentiment Analysis  eBooks & eLearning

Posted by nebulae at April 11, 2017
A Practical Guide to Sentiment Analysis

Erik Cambria, "A Practical Guide to Sentiment Analysis"
English | ISBN: 3319553925 | 2017 | 196 pages | PDF | 2 MB

Sentiment Analysis for PTSD Signals  eBooks & eLearning

Posted by First1 at Oct. 7, 2017
Sentiment Analysis for PTSD Signals

Sentiment Analysis for PTSD Signals by Vadim Kagan, Edward Rossini, Demetrios Sapounas
English | October 25th, 2013 | ASIN: B00G66H9P6, ISBN: 1461430968 | 76 pages | EPUB | 1.19 MB

This book describes a computational framework for real-time detection of psychological signals related to Post-Traumatic Stress Disorder (PTSD) in online text-based posts, including blogs and web forums. Further, it explores how emerging computational techniques such as sentiment mining can be used in real-time to identify posts that contain PTSD-related signals, flag those posts, and bring them to the attention of psychologists, thus providing an automated flag and referral capability.

Sentiment Analysis with Recurrent Neural Networks in TensorFlow  eBooks & eLearning

Posted by naag at Dec. 23, 2017
Sentiment Analysis with Recurrent Neural Networks in TensorFlow

Sentiment Analysis with Recurrent Neural Networks in TensorFlow
MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 3 Hours | 520 MB
Genre: eLearning | Language: English

Recurrent neural networks (RNNs) are ideal for considering sequences of data. In this course, you'll explore how word embeddings are used for sentiment analysis using neural networks.

A Practical Guide to Sentiment Analysis  eBooks & eLearning

Posted by roxul at March 13, 2018
A Practical Guide to Sentiment Analysis

Erik Cambria, "A Practical Guide to Sentiment Analysis"
English | ISBN: 3319553925 | 2017 | 196 pages | EPUB | 1 MB

The #1 Python Data Scientist: Sentiment Analysis & More  eBooks & eLearning

Posted by Sigha at Oct. 24, 2020
The #1 Python Data Scientist: Sentiment Analysis & More

The #1 Python Data Scientist: Sentiment Analysis & More
Video: .mp4 (1280x720, 30 fps(r)) | Audio: aac, 48000 Hz, 2ch | Size: 6.16 GB
Genre: eLearning Video | Duration: 105 lectures (16 hour, 37 mins) | Language: English

Build Projects with Machine Learning, Text Classification, TensorFlowNumPy, PyPlot, Pandas, and More in Google Colab…

Sentiment Analysis and Deep Learning  eBooks & eLearning

Posted by hill0 at Jan. 8, 2023
Sentiment Analysis and Deep Learning

Sentiment Analysis and Deep Learning
English | 2023 | ISBN: 9811954429 | 987 Pages | PDF (True) | 32 MB

Sentic Computing: A Common-Sense-Based Framework for Concept-Level Sentiment Analysis  eBooks & eLearning

Posted by AvaxGenius at Nov. 15, 2024
Sentic Computing: A Common-Sense-Based Framework for Concept-Level Sentiment Analysis

Sentic Computing: A Common-Sense-Based Framework for Concept-Level Sentiment Analysis by Erik Cambria , Amir Hussain
English | PDF (True) | 2015 | 196 Pages | ISBN : 3319236539 | 4.1 MB

This volume presents a knowledge-based approach to concept-level sentiment analysis at the crossroads between affective computing, information extraction, and common-sense computing, which exploits both computer and social sciences to better interpret and process information on the Web.