Sentiment Analysis with LSTM | Deep Learning with Keras | Neural Networks | Project#8

Video Description

We shall train three separate Neural Networks, namely: a Simple Neural Net, a Convolutional Neural Net and a Long Short Term Memory Neural Net. LSTM networks are actually considered to be quite suitable for handling NLP problems, and by the end of this video, you will understand why. Sentiment Classification LSTM Model we shall be training as part of this tutorial is so good that it not only predicts the user movie review sentiment as positive/negative, it also does a fabulous job in predicting IMDb Rating itself corresponding to these reviews with mind blowing accuracy. 🔥 During the course of next ~25mins, we shall discuss: a. Word Embedding (which is a powerful feature extraction technique), b. Intuition on various Neural Network approaches (Simple / CNN /LSTM), c. Concept of Overfitting (that happens when a model memorises training data, rather than understanding general distribution) d. And, of course, our high-level solution architecture for training our Sentiment Classification Models 🔥 Sections: 00:00 Introduction 02:17 Solution Architecture 03:50 Word Embeddings, Neural Networks & Overfitting 08:56 Free Skillcate Project Toolkit 09:55 Code: Intro 11:42 Code: Data Preprocessing 13:44 Code: Tokenizer & Embedding Layer 15:50 Code: Simple NN Training 17:50 Code: CNN Training 19:27 Code: LSTM Training 21:03 Having fun with Model 22:59 Updates on Free 1:1 Mentoring 🔥 Important Links: Toolkit link: https://drive.google.com/drive/folders/1TK9k41RT8Nf3IhzerNWHpEqWztsk2gAP?usp=sharing Sentiment Analysis Project based Review Classification Project from Skillcate: https://youtu.be/zwR6M5zpnWs Sentiment Analysis Project (End-to-end) with ML Model Building + Deployment (using Flask): - Model Building: https://youtu.be/lKAdxN0qrgk (Part-1) - Model Deployment: https://youtu.be/KEQCVwJU5KU (Part-2) GitHub Repo Link: https://github.com/skillcate/movie-sentiment-analysis-with-deep-neural-networks.git 🔥 Do like, share & subscribe to our channel. Keep in touch: Email: [email protected] Website: https://www.skillcate.com Facebook: https://www.facebook.com/groups/mlprojects Telegram: https://t.me/skillcate