About This Course
Learning to do sentiment analysis would make yourself invaluable to any company, especially those which are interested in quality assurance of their products and those working with business intelligence.
In this course, you will learn how to plug a system into your existing pipelines to do sentiment analysis of any text you can throw at it. In the beginning, we will introduce a less than 60 line sentiment analysis engine that can perform industry grade sentiment analysis. We then spend the rest of the course explaining these very powerful 60 lines so that you have a thorough understanding of the code.
What this course covers:
- Understanding how to write industry grade sentiment analysis engines with very little effort
- Basics of machine learning with minimal math
- Understand not only the theoretical and academic aspects of sentiment analysis but also how to use it in your own field — real world sentiment analysis
- Tips on avoiding mistakes made by new-comers to the field and the best practices to get you to your goal with minimal effort
Our Promise to You
By the end of this course, you will have learned sentiment analysis using Python and Deep Learning.
30 Day Money Back Guarantee. If you are unsatisfied for any reason, simply contact us and we’ll give you a full refund. No questions asked.
Get started today and learn more about sentiment analysis using Python.
|Section 1 - Introduction|
|Bird’s Eye View Of Deep Sentiment Analysis||00:00:00|
|MNIST Dataset Description||00:00:00|
|Learning And Prediction Pipeline||00:00:00|
|Section 2 - Bare Essentials Of Theory|
|Machine Learning Pipeline||00:00:00|
|Neural Networks – A Modular Approach||00:00:00|
|Recap And Supporting Talk||00:00:00|
|Section 3 - Getting Started With Keras|
|Windows Installation And Hurdles||00:00:00|
|Mac And Linux Installation||00:00:00|
|Keras : Data Preparation||00:00:00|
|Learning And Evaluation With Keras||00:00:00|
|Section 4 - Sentiment Analysis Case Study|
|Understanding The Sentiment Data||00:00:00|
|Structure Of Data For Deep Learning||00:00:00|
|Model, Embedding And Applying To Real World||00:00:00|
|Section 5 - Convolutional Neural Networks With Keras|
|Basics of Convolutional Neural Networks||00:00:00|
|ConvNet With Keras||00:00:00|
|Pooling And Translation Invariance||00:00:00|
|Dropout And Regularization||00:00:00|
|Using The Functional API With CNN||00:00:00|
|Section 6 - Revisiting The Sentiment Analysis Model|
|CNN, LSTM And Other Models For Sentiment Analysis||00:00:00|
|Section 7 - Finishing Up|
|Saving And Loading Model Weights||00:00:00|
|Parting Words And Future Directions||00:00:00|