Customized Sentiment Analysis | Transfer Learning Using Tensorflow with Hugging Face | Deep Learning
Transfer learning is also called pretrained model fine-tuning. It refers to training a model with a small dataset while leveraging the stored information from a model trained with a large dataset for another task. In this tutorial, we will talk about how to use a small review dataset to build a sentiment prediction model while leveraging a pretrained transformer model. We will cover:
👉 What are the benefits of building a customized sentiment analysis transfer learning model?
👉 How to build a transfer learning model for sentiment analysis?
👉 How to make predictions for a transfer learning model and evaluate the prediction accuracy?
👉 How to save a fine-tuned transfer learning model and reload it for sentiment prediction?
👉 How to make the transfer learning training process faster for a large dataset?
⏰ Timecodes ⏰
0:00 - Intro
0:40 - Step 1: Benefits of Transfer Learning for Sentiment Analysis
2:14 - Step 2: Sentiment Analysis Algorithms
2:54 - Step 3: Install And Import Python Libraries
3:21 - Step 4: Download And Read Data
5:01 - Step 5: Train Test Split
5:14 - Step 6: Tokenize Text
6:49 - Step 7: Compile Transfer Learning Model for Sentiment Analysis
8:00 - Step 8: Train Transfer Learning Model for Sentiment Analysis
9:01 - Step 9: Sentiment Analysis Transfer Learning Model Prediction and Evaluation
9:57 - Step 10: Save and Load Model
10:30 - Step 11: Sentiment Model Using Transfer Learning on Large Dataset
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🎞️ NLP playlist: • NLP
📺 Videos mentioned in the video
TextBlob vs. VADER for Sentiment Analysis Using Python: • TextBlob vs. VADER For Sentiment Anal...
Sentiment Analysis: Hugging Face Zero-shot Model vs Flair Pre-trained Model: • Sentiment Analysis | Hugging Face Zer...
Google Colab Tutorial for Beginners: • Google Colab Tutorial For Beginners
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