Text Classification and Sentiment Analysis with NLP Models Training Course
Course Overview
This course provides in-depth knowledge and practical skills to implement text classification and sentiment analysis using Natural Language Processing (NLP) models. Participants will explore machine learning and deep learning approaches for text analysis, including logistic regression, Naïve Bayes, and Transformer-based models like BERT. Hands-on exercises and case studies will prepare attendees to build, evaluate, and deploy models for diverse text analysis applications.
Format of Training
- Instructor-led sessions
- Hands-on lab activities with NLP tools and frameworks
- Practical demonstrations of text classification workflows
- Group discussions and real-world case studies
Course Objectives
- Understand the fundamentals of text classification and sentiment analysis.
- Explore traditional machine learning models such as Naïve Bayes and SVMs.
- Gain hands-on experience with deep learning models like LSTMs and BERT.
- Learn preprocessing techniques for text data, including tokenization and embeddings.
- Build and evaluate models for sentiment analysis and classification tasks.
- Identify real-world applications of text analysis in business and research.
- Develop workflows for deploying NLP models in production environments.
Prerequisites
- Basic understanding of Python programming
- Familiarity with machine learning concepts
- No prior experience with NLP required
- Interest in analyzing text data for actionable insights
Course Outline
Day 1: Fundamentals and Traditional Models
Session 1: Introduction to Text Classification and Sentiment Analysis
- Overview of classification tasks and sentiment analysis
- Key applications and use cases in industries
Session 2: Preprocessing for Text Analysis
- Tokenization, stemming, lemmatization, and stopword removal
- Hands-on lab: Preprocessing text data for classification tasks
Session 3: Traditional Machine Learning Approaches
- Logistic regression, Naïve Bayes, and support vector machines
- Hands-on lab: Implementing a Naïve Bayes model for sentiment classification
Day 2: Deep Learning Models for Text Analysis
Session 1: Introduction to Deep Learning for NLP
- Word embeddings and neural network architectures
- Hands-on lab: Using word2vec and GloVe embeddings
Session 2: Recurrent Neural Networks (RNNs) and LSTMs
- Building models for sequence data
- Hands-on lab: Implementing an LSTM for text classification
Session 3: Transformer-Based Models
- Introduction to BERT and its applications
- Practical demonstration: Fine-tuning BERT for sentiment analysis
Day 3: Evaluation, Deployment, and Real-World Applications
Session 1: Model Evaluation and Optimization
- Metrics for text classification and sentiment analysis
- Hands-on lab: Evaluating models with precision, recall, and F1-score
Session 2: Deploying NLP Models
- Creating APIs for model deployment
- Hands-on lab: Deploying a sentiment analysis model with Flask
Session 3: Real-World Case Studies and Final Project
- Applications in social media, e-commerce, and customer feedback
- Group activity: Building and presenting a text classification pipeline
- Feedback and discussion: Future trends in text analysis
Bespoke Option
We are open to customizing this program to align with your specific learning objectives. If your team has particular goals or areas they wish to focus on, we would be happy to tailor the course outline to meet those needs and ensure the program supports the achievement of your desired outcomes.
Need help with the right course to choose?
support@skillvotech.com
Explore more opportunities
- Duration: 1 Day
- 4.5 Ratings
Introduction to Natural Language Processing for Beginners Training Course
- Duration: 2 Days
- 4.5 Ratings
Sentiment Analysis and Opinion Mining with NLP Training Course
- Duration: 2 Days
- 4.5 Ratings
Essential Text Preprocessing Techniques for NLP Training Course
- Duration: 3 Days
- 4.5 Ratings
NLP with Python: Using NLTK, SpaCy, and Gensim Training Course
- Duration: 4 Days
- 4.5 Ratings
Deep Learning for NLP: Exploring RNNs, LSTMs, and GRUs Training Course
- Duration: 5 Days
- 4.5 Ratings
Transformers in NLP: From BERT to GPT Models Training Course