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Sentiment Analysis Through Deep Learning with Keras & Python
Introduction
Bird’s Eye View of Deep Sentiment Analysis (13:49)
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)
Keras Data Preparation (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 Network 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)
Source Code
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Pooling and Translation Invariance
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