About This Course
Skills you'll learn from this course
- done_all Creating a dataset of application-specific expected outcomes for Natural Language Understanding
- done_all Training a TensorFlow-Keras based model for Natural Language Understanding
- done_all Matching text inputs with expected intents with Natural Language Understanding
- done_all Model accuracy/performance calculations and optimization methods
- done_all Model modularization for integration with Robot Operating System
Join "Natural Language Understanding with Python, Neural Networks-TensorFlow and ROS Integration" on Robociti to improve your Speech Processing skills and learn how to create a Natural Language Understanding (NLU) module that can act as the final stage in a Speech Recognition pipeline on a live or pre-recorded audio stream, matching recognized words or sentences to a set of expected outcomes for use in a specific application. To achieve this, popular frameworks like Python programming for dataset creation, TensorFlow and Keras for Neural Network model construction and fast deployment, and ROS (Robot Operating System) for further integration with other modules in larger AI & Robotics projects are utilized. Firstly, the process of creating a dataset of the expected outcomes based on a specific application is presented, along with any data processing required. Then, the method for using the dataset constructed to train a suggested Neural Network Model based on TensorFlow and Keras is analyzed, along with the way to calculate the accuracy of the model produced and tips about how to optimize the training process. Finally, the module is wrapped in the ROS framework for the integration in a larger Speech Recognition application and students work on improving the final result.
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Course Features
- check_circle Programming Environment
- check_circle Jupyter Notebook
- check_circle Forum & Support
Course Chapters
Dataset Creation
Robot Management
WorkSpace Setup
NLP introduction
Dataset generation
Dataset preparation
Running inferences
Ros integration
Course Completion