Welcome to our Advanced Sentiment Analysis course. In this comprehensive guide, we will dive deep into the intricacies of sentiment analysis, a key aspect of natural language processing. Sentiment analysis is the process of determining whether a piece of text is positive, negative, or neutral. This skill is highly sought after in various fields, including marketing, social media, and customer service.
Course Overview
- Duration: 12 weeks
- Level: Intermediate to Advanced
- Prerequisites: Basic knowledge of Python and machine learning
Course Content
Introduction to Sentiment Analysis
- Understanding the concept and importance of sentiment analysis
- Common applications of sentiment analysis
Data Preparation and Cleaning
- Collecting and preparing text data
- Cleaning and preprocessing text data
Feature Extraction
- Tokenization
- Stemming and lemmatization
- TF-IDF and word embeddings
Modeling Techniques
- Traditional machine learning models
- Deep learning models
- Evaluation metrics
Real-World Applications
- Sentiment analysis on social media
- Sentiment analysis in customer reviews
- Sentiment analysis in financial reports
Course Materials
Textbooks:
- "Text Mining and Analytics" by Ian H. Witten and Eibe Frank
- "Deep Learning for Natural Language Processing" by Colah's Blog
Online Resources:
Hands-On Projects
- Project 1: Sentiment analysis on movie reviews
- Project 2: Sentiment analysis on Twitter data
- Project 3: Sentiment analysis on customer reviews
Enroll Now
Ready to embark on your journey to mastering advanced sentiment analysis? Enroll now and join our growing community of data science enthusiasts!
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