Course description
Natural Language Processing | Comprehensive NLP
This “skills-centric” course is about 50% hands-on lab and 50% lecture, with extensive practical exercises designed to reinforce fundamental skills, concepts and best practices taught throughout the course. Our engaging instructors and mentors are highly-experienced practitioners who bring years of current, modern "on-the-job" modern deep learning experience into every classroom and hands-on project. In this course Students will explore:
Hands-on Projects
- Neural Text Classification. Develop a deep learning model to classify the sentiment of movie reviews as either positive or negative.
- Neural Language Modeling. Develop a neural language model on the text of Plato in order to generate new tracts of text with the same style and flavor as the original.
- Neural Photo Captioning. Develop a model to automatically generate a concise description of ad hoc photographs.
- Neural Machine Translation. Develop a model to translate sentences of text in German to English.
Neural Network Models
- Neural Bag-of-Words. Develop neural network models that model text as a bag-of-words where word order is ignored.
- Neural Word Embedding. Develop neural network models that model text using a distributed representation.
- Embedding + CNN. Develop deep learning models that combine word embedding representations with convolutional neural networks.
- Encoder-Decoder RNN. Develop recurrent neural networks that use the encoder-decoder architecture.
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Who should attend?
This in an intermediate and beyond-level course is geared for experienced developers or others (with prior Python experience) intending to start using learning about and working with Natural Language Processing soon after they attend this course. Attendees should be experienced developers who are comfortable with Python programming. Students should also be able to navigate Linux command line, and who have basic knowledge of Linux editors (such as VI / nano) for editing code.
Students should have attended or have incoming skills equivalent to those in this course:
- Strong basic Python Skills and basic deep learning knowledge.
- Prior working experience with Keras is also useful
Training content
Foundations
- Natural Language Processing
- Deep Learning
- Promise of Deep Learning for Natural Language
- How to Develop Deep Learning Models With Keras
Data Preparation
- How to Clean Text Manually and with NLTK
- How to Prepare Text Data with scikit-learn
- How to Prepare Text Data With Keras
Bag-of-Words
- The Bag-of-Words Model
- Prepare Movie Review Data for Sentiment Analysis
- Neural Bag-of-Words Model for Sentiment Analysis
Word Embeddings
- The Word Embedding Model
- How to Develop Word Embeddings with Gensim
- How to Learn and Load Word Embeddings in Keras
Text Classification
- Neural Models for Document Classification
- Develop an Embedding + CNN Model
- Develop an n-gram CNN Model for Sentiment Analysis
Language Modeling
- Neural Language Modeling
- Develop a Character-Based Neural Language Model
- How to Develop a Word-Based Neural Language Model
- Develop a Neural Language Model for Text Generation
Image Captioning
- Neural Image Caption Generation
- Neural Network Models for Caption Generation
- Load and Use a Pre-Trained Object Recognition Model
- How to Evaluate Generated Text With the BLEU Score
- How to Prepare a Photo Caption Dataset For Modeling
- Develop a Neural Image Caption Generation Model
Neural Machine Translation
- Neural Machine Translation
- Encoder-Decoder Models for NMT
- Configure Encoder-Decoder Models for NMT
- How to Develop a Neural Machine Translation Model
Costs
- Price: $2,595.00
- Discounted Price: $1,686.75
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Trivera Technologies
Trivera Technologies is a IT education services & courseware firm that offers a range of wide professional technical education services including: end to end IT training development and delivery, skills-based mentoring programs,new hire training and re-skilling services, courseware licensing and...