Project analyzes Amazon Stock data using Python. Feature Extraction is performed and ARIMA and Fourier series models are made. LSTM is used with multiple features to predict stock prices and then sentimental analysis is performed using news and reddit sentiments. GANs are used to predict stock data too where Amazon data is taken from an API as Generator and CNNs are used as discriminator.

Chinese Sentiment Analysis 中文文本情感分析

Using Technical, Fundamental, and Sentimental Analysis with Machine Learning

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Sentimental Analysis with Naver movie ratings

Twitter Sentiment Analysis using #tag, words and username

Research project implementation for the ICAIF'21 publication and Master's Thesis. ITS-SentARL => Intelligent Trading Systems: A Sentiment-Aware Reinforcement Learning Approach

YouTube Sentiment Analysis is a web application that analyzes the sentiment of YouTube comments, providing insights into comment sentiment using VADER sentiment analysis and interactive visualizations.

data, code, pre-trained models and experiment results for "SEntiMoji: An Emoji-Powered Learning Approach for Sentiment Analysis in Software Engineering"

Bidirectional GRU with attention mechanism on imdb sentimental analysis dataset

This notebook provides some skills to perform financial analysis on economical data.

Sentimental analysis using keras in python

This project performed sentimental analysis based on opinion words (like good, bad, beautiful, wrong, best, awesome, etc) of selected opinion target ( like product name for amazon product reviews).

Sentiment Analysis of product based reviews using Machine Learning Approaches. This is my Final Year B.Tech Project, 2018.

R and Data Files from my YouTube Channel

Natural Language Processing

Python Script for sentimental analysis of tweets.

This Repository Contains Different ways to do sentimental Analysis

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Build a model to classify text as positive, negative, or neutral. Apply NLP techniques for preprocessing and machine learning for classification. Aim for accurate sentiment prediction on various text formats.

This script uses Python and Redis with Twitter API to run a fully automated twitter account.

Sentimental Analysis using LingPipe, Mogodb and MapReduce

Sentimental Analysis of Twitter Posts and Recommending Psychological Reports Based on them

A Multi-modal Framework for Sentimental Analysis of Meme

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We-heal is an Artificial intelligence powered Chat-bot for people who are suffering from Depression, anxiety and other mental cloths. It uses sentimental analysis and natural language processing to give the best answers possible My chat-bot will talk to the person efficiently and will also give suggestion to upscale mental and emotional state of patient. My chat-bot’s Current results show accuracy of 84.14% on the training data, accuracy of 83.32% on the cross validation data and accuracy of 60.17% on the test data. The USC ICT Virtual Human Toolkit enables one to create virtual humans and environments in which these virtual humans can interact with users. With technologies like MultiSense, Nonverbal Behaviour Generator and SmartBody, it enables virtual humans to display various body gestures and facial expressions according to the environment and state of the conversation. We live in a world of 8 billion people and almost 60-70% of us suffers from depression or anxiety for at-least once in life, i feel that this mental issues are not seen and voices of people suffering from it are not heard properly. Having a similar experience, i can say a person suffering from such issues want something or someone to clear their mind and help them revive. This is my contribution to this health issue .

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An AI project where we do web scrapping from Twitter API, find the sentimental analysis using bag-of-word model, & store it in a csv file.

BERT-based Aspect-Based Sentiment Analysis for Airline Reviews

Facial Expression Recognition using Deep Learning. Keywords: Python, CNN, Image Classification, Keras, TensorFlow, Emotion Detection.