Opinion Mining

Transfer Learning with Transformers you own this product

This project is part of the liveProject series End-to-End Deep Learning for Opinion Mining
prerequisites
basics of scikit-learn, PyTorch, and Matplotlib
skills learned
model monitoring • transfer learning using state-of-the-art NLP model • model diagnostics
Winnie and Eyan Yeung
1 week · 4-6 hours per week · INTERMEDIATE
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liveProject This project is part of the liveProject series End-to-End Deep Learning for Opinion Mining liveProjects give you the opportunity to learn new skills by completing real-world challenges in your local development environment. Solve practical problems, write working code, and analyze real data—with liveProject, you learn by doing. These self-paced projects also come with full liveBook access to select books for 90 days plus permanent access to other select Manning products. $19.99 $29.99 you save $10 (33%)
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In this liveProject, you’ll use transformer-based deep learning models to predict the tag of Reddit subreddits to help your company understand what its customers are saying about them. Transformers are the state of the art, large-scale deep language models pretrained on a huge corpus of text, and are capable of understanding the complexity of grammar really well. You’ll train this model on your own data set, and tune its hyperparameters for the best results.

This project is designed for learning purposes and is not a complete, production-ready application or solution.

book resources

When you start your liveProject, you get full access to the following books for 90 days.

project authors

Man Wai Winnie Yeung
Winnie Yeung is a full-stack senior data scientist at Visa in the San Francisco Bay Area, working on developing and deploying risk-related machine learning solutions. She earned her master’s in analytics at Georgia Institute of Technology and has 3 years of experience working on natural language processing projects in the investment industry. She actively contributes to the open-source community by creating a neural machine translation package on PyPI, as well as giving talks at PyCon Hong Kong.
Eyan Yeung
Eyan Yeung, PhD is a full-stack data scientist in New Jersey using various machine learning models and data science techniques to fight adversarial abuse. She earned her PhD in molecular biology at Princeton University, having used unsupervised machine learning techniques and built mathematical models to analyze large-scale biological datasets. She has experience completing multiple end-to-end projects in image classification and natural language processing.

prerequisites

This liveProject is for confident Python programmers interested in taking their first steps into data analysis for marketing. To begin this liveProject you will need to be familiar with the following:


TOOLS
  • Basics of scikit-learn
  • Basic PyTorch
  • Basics of Matplotlib
  • Basics of Git
TECHNIQUES
  • Basic knowledge of neural networks
  • Basic concepts in machine learning

you will learn

In this liveProject, you’ll learn to apply transfer learning and master techniques to help enhance model accuracy.


  • Data preprocessing for PyTorch models
  • Data augmentation
  • Model monitoring
  • Transfer learning using state-of-the-art NLP model
  • Model diagnostics
  • Version control of models
  • Generate inferences on unseen data using a fine-tuned model

features

Self-paced
You choose the schedule and decide how much time to invest as you build your project.
Project roadmap
Each project is divided into several achievable steps.
Get Help
While within the liveProject platform, get help from other participants and our expert mentors.
Compare with others
For each step, compare your deliverable to the solutions by the author and other participants.
book resources
Get full access to select books for 90 days. Permanent access to excerpts from Manning products are also included, as well as references to other resources.
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