TOPIC
Big Data infrastructure and technologies
SUBTOPIC
Machine learning
LANGUAGE
Spanish
ENROLL
On Demand
DURATION
4 days (16 h)
TRAINER
ITI
Develop your own real NLP application from scratch: using the best tools for its development and cloud services to deploy it.
Program:
Unit 1. Introduction to NLP
Unit 2. Uses I
Unit 3. Pre-trained models
Unit 4. Uses II
Unit 5. Building an NLP service in the cloud
Program:
Unit 1. Introduction to NLP
Unit 2. Uses I
Unit 3. Pre-trained models
Unit 4. Uses II
Unit 5. Building an NLP service in the cloud
Keywords:
Artificial Intelligence, Machine Learning, Natural Language Processing, Sentiment analysis, Text mining
LEARNING OUTCOMES
Knowledge of the main techniques for cleaning and processing textual data.
Knowledge of the main classic and advanced tokenization techniques (WPE, BPE).
Knowledge of classical text representation techniques (TF-IDF).
Knowledge of advanced text rendering techniques (LSTM, Transformers).
Know and apply transfer learning techniques to textual documents.
Construction of services dedicated to text analysis.
Know and apply the different applications of NLP: sentiment analysis, classification, topic modeling, entity detection, anonymization
PRE-REQUISITES
Python, Basic ML
TARGET AUDIENCE
Professional Data Science
COURSE TYPE
Lecture and Hands-on
MATERIALS
Slides, practical exercises
