Course Overview
This course introduces the products and solutions to NLP problems on Google Cloud. It also explores the processes, techniques, and tools to develop an NLP project with neural networks using Vertex AI and TensorFlow.
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Prerequisites
Understanding one or more of the following: -
- Machine learning models such as CNN, RNN, DNN, and LSTM
- The basic syntax of Python -The basic idea of TensorFlow and Keras
Audience Profile
- Professional ML engineers, ML developers, data engineers, and data scientists who are in the field of natural language processing
- IT decision makers evaluate the value of NLP brought to the organization.
Learning Objectives
- Recognize the NLP products and the solutions on Google Cloud.
- Create an end-to-end NLP workflow by using AutoML with Vertex AI.
- Build different NLP models, including DNN, RNN, LSTM, and GRU, by using TensorFlow.
- Recognize advanced NLP models such as encoder-decoder, attention mechanism, transformers, and BERT.
- Understand transfer learning and apply pre-trained models to solve NLP problem
Content Outline
This module discusses the reasons to learn NLP from Google and provides an introduction of the course goals and structure.
This module gives an overview of the NLP architecture on Google Cloud. It examines the NLP history, the NLP APIs such as the Dialogflow API, and the NLP solutions like Contact Center AI and Document AI.
This module explores AutoML and custom training, two options for developing an NLP project with Vertex AI. Additionally, the module introduces an end-to-end NLP workflow and provides a hands-on lab to apply the workflow to solve a text classification task with AutoML.
This module describes the process of preparing text data in NLP and introduces the significant categories of text representation techniques.
This module describes NLP models, including ANN, DNN, RNN, LSTM, and GRU. It also introduces the benefits and disadvantages of each model.
This module introduces NLP's state-of-the-art technologies and models: encoder-decoder, attention mechanism, transformers, BERT, and significant language models.
This module reviews the topics covered in the course and provides additional resources for further learning.
FAQs
A: Google search mainly uses natural language processing in the following areas: Interpretation of search queries. Classification of subject and purpose of documents. Entity analysis in papers, search queries, and social media posts.
A: Natural language processing (NLP) uses machine learning to reveal the structure and meaning of the text. With natural language processing applications, organizations can analyze text and extract information about people, places, and events to understand social media sentiment and customer conversations better.
A: Google's Natural Language Processing (NLP) research focuses on scaling, cross-linguistic, and cross-domain algorithms. Google uses our technologies in a variety of ways that affect the user experience in search, mobile, applications, advertisements, translate, and other areas.
A: Radiant has highly intensive selection criteria for Technology Trainers & Consultants who deliver training programs. Our trainers & consultants undergo a rigorous technical and behavioral interview and assessment process before they are onboarded in the company.
Our Technology experts/trainers & consultants carry deep-dive knowledge in the technical subject & are certified by the OEM.
Our training programs are practically oriented with 70% – 80% hands-on training technology tools. Our training program focuses on one-on-one interaction with each participant, the latest content in the curriculum, real-time projects, and case studies during the training program.
Our faculty will quickly provide you with the knowledge of each course from the fundamental level, and you are free to ask your doubts at any time from your respective faculty.
Our trainers have the patience and ability to explain complex concepts simplistically with depth and width of knowledge.
To ensure quality learning, we provide support sessions even after the training program.
A: To attend the training session, you should have operational Desktops or Laptops with the required specification and a good internet connection to access the labs.
A: We recommend you attend the live session to practice & clarify the doubts instantly and get more value from your investment. However, if, due to some contingency, you have to skip the class, Radiant Techlearning will help you with the recorded session of that particular day. However, those recorded sessions are not meant only for personal consumption and NOT for distribution or any commercial use.
A: Radiant Techlearning has a data center containing a Virtual Training environment for participants’ hand-on-practice.
Participants can easily access these labs over Cloud with the help of a remote desktop connection.
Radiant virtual labs allow you to learn from anywhere and in any time zone.
A: The learners will be enthralled as we engage them in the natural world and industry Oriented projects during the training program. These projects will improve your skills and knowledge and give you a better experience. These real-time projects will help you a lot in your future tasks and assignments.