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Sentiment Analysis through Deep Learning with Keras and Python
Introduction to Sentiment Analysis with Deep Learning
Bird’s Eye View of Deep Sentiment Analysis (13:49)
Resource Download
MNIST Dataset Description (8:11)
Learning and Prediction Pipeline (7:01)
Bare Essentials of Theory
Machine Learning Pipeline (9:13)
Regression (13:01)
Neural Networks - a Modular Approach (14:29)
Recap and Supporting Talk (2:43)
Getting Started with Keras
Windows installation and hurdles (6:55)
Mac and Linux installation (3:41)
Data Preparation with Keras (10:10)
Learning and Evaluation with Keras (10:32)
Sentiment Analysis Case Study
Understanding the Sentiment Data (10:36)
Structure of Data for Deep Learning (4:37)
Model, Embedding and Applying to Real World (10:41)
Convolutional Neural Networks with Keras
Basics of Convolutional Neural Networks (10:13)
ConvNet with Keras (8:30)
Pooling and Translation Invariance (4:25)
Dropout and Regularization (3:51)
Using the functional API with CNN (4:27)
Revisiting the Sentiment Analysis Model
CNN, LSTM and Other Models for Sentiment Analysis (5:57)
Finishing Up
Saving and loading model weights (6:30)
Parting words and future directions (3:48)
Bird’s Eye View of Deep Sentiment Analysis
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