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Sentiment Analysis with LSTM and Keras in Python (Updated)


Sentiment Analysis with LSTM and Keras in Python (Updated)
Sentiment Analysis with LSTM and Keras in Python
Video: .mp4 (1280x720, 30 fps(r)) | Audio: aac, 44100 Hz, 2ch | Size: 924 MB
Genre: eLearning Video | Duration: 18 lectures (2 hour, 46 mins) | Language: English


Learn how to do Sentiment Classification using LSTM in Keras and Python
What you'll learn
What is Sentiment Analysis
What are RNN and LSTMs
How to apply LSTM in Keras for Sentiment Analysis
Requirements
Basic Python programming
Description
Sentiment analysis ( or opinion mining or emotion AI) refers to the use of natural language processing(NLP), text analysis, computational linguistics, and biometrics to systematically identify, extract, quantify, and study affective states and subjective information. Sentiment analysis is widely applied to voice of the customer materials such as reviews and survey responses, online and social media, and healthcare materials for applications that range from marketing to customer service to clinical medicine.
Simple RNNs are not good in capturing long-term dependencies. In this course we unleash the power of LSTM (Long Short Term memory) using Keras.
Who this course is for:
Data scientists
Machine Learning Engineers
Applied Scientists
Research Scientists
College Students

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