MP4 | Video: h264, 1280x720 | Audio: AAC, 48 KHz, 2 Ch

Genre: eLearning | Language: English + .srt | Duration: 18 lectures (2 hour, 46 mins) | Size: 924 MB

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