Natural Language Processing Course
- 1-Day
- Online, Instructor-led, Interactive, Practical
- Locations
- PCWorkshops Course Certificate on completion
- Natural Language Processing Course Notes
- Natural Language Processing Code Examples
- Practical Natural Language Processing Course exercises, Natural Language Processing Course Revision work
- After the course: 1-Hour personalised online revision session optional, on request
Natural Language Processing Basics
Hands-on, Practical Course, Instructor-led Course.
Online
1 day
In classroom at on request.
Natural Language Processing Course description
This course covers Natural Language Processing principles.
What You'll Learn: (
Hands-On Learning )
Comprehensive Coverage: Basic, Intermediate, and Advanced NLP concepts.
Tools and Libraries: NLTK, regex, Stanford NLP, TextBlob, and data cleaning techniques.
Entity Resolution: Techniques for identifying and merging different representations of the same entity.
Feature Extraction: Converting text into features for analysis.
Word Embedding: Understanding and implementing word embedding techniques.
Word2Vec and GloVe: Mastering these popular word embedding models.
Word Sense Disambiguation: Techniques to determine the meaning of words in context.
Speech Recognition: Basics of converting speech to text.
String Similarity: Methods for comparing the similarity between two strings.
Language Translation: Techniques for automatic translation between languages.
Computational Linguistics: Applying computational techniques to linguistic problems.
Classification Techniques: Using Random Forest, Naive Bayes, and XGBoost for text classification.
Deep Learning Classifications: Implementing classifications with TensorFlow (tf.keras).
Sentiment Analysis: Determining the sentiment of text data.
Clustering: K-means clustering techniques for text data.
Topic Modeling: Identifying topics within a corpus of text.
Model Evaluation: Understanding Bias vs. Variance to evaluate model performance.