Deep Learning for NLP (Natural Language Processing) Training Course
Deep Learning (DL) is a specialized branch of Machine Learning (ML).
Python, a widely adopted programming language, offers extensive libraries specifically designed for Deep Learning in the realm of Natural Language Processing.
Deep Learning for NLP enables machines to comprehend and process language, ranging from basic to highly complex structures. Key capabilities include machine translation and generating descriptive captions for images.
Through this instructor-led, live training, participants will master the use of Python libraries for NLP by building an application that analyzes a set of images and automatically generates captions.
Upon completion of this training, participants will be able to:
- Design and implement Deep Learning solutions for NLP using Python libraries.
- Write Python code to process large volumes of images and extract relevant keywords.
- Develop Python code that creates captions based on the identified keywords.
Course Format
- A blend of lectures, interactive discussions, exercises, and extensive hands-on practice.
Course Outline
Introduction to Deep Learning for NLP
Distinguishing between various types of DL models
Utilizing pre-trained versus custom-trained models
Extracting meaning from text using word embeddings and sentiment analysis
Understanding how Unsupervised Deep Learning operates
Installing and configuring Python Deep Learning libraries
Leveraging the Keras DL library on top of TensorFlow to enable caption generation in Python
Working with Theano (a numerical computation library) and TensorFlow (a general-purpose and linguistic library) as extended DL frameworks for caption creation
Rapidly experimenting with Deep Learning using Keras atop TensorFlow or Theano
Developing a simple Deep Learning application in TensorFlow to add captions to an image collection
Troubleshooting common issues
Overview of other specialized DL frameworks
Deploying your DL application
Accelerating Deep Learning using GPUs
Closing remarks
Requirements
- Familiarity with Python programming.
- General understanding of Python libraries.
Audience
- Programmers with an interest in linguistics.
- Developers seeking a deeper understanding of Natural Language Processing (NLP).
Open Training Courses require 5+ participants.
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