Advanced NLP Projects with TensorFlow 2.0 [Video]

More Information
  • Create powerful NLP-based deep learning models with TensorFlow 2.0
  • Learn to implement Word2Vec and seq2seq
  • Design applications that deliver scores and state-of-the-art visualizations
  • Build a text classification system that can be used for spam detection, sentiment analysis, and similar problems
  • Build a neural machine translation system
  • Understand how to extract words to classify topics

Natural Language Processing (NLP) is the field of Artificial Intelligence (AI) that deals with text analysis and understanding. Some fields in which NLP is widely used are sentiment classification, spam detection, and topic detection. Deep learning is one of the tools that help us solve NLP problems.

This course will get you started with real-world NLP projects and you will learn how to get the best insights from your text data. We will be building and training models in real-world projects and will focus on interactions between computers and humans with TensorFlow 2.0. Together, we will undertake a deep-dive into a collection of textual data sources, writing a Jupyter notebook step by step until we obtain actionable insights and powerful visualizations.

By the end of the course, you will be able to build and implement your own NLP techniques and projects effectively, easily, and confidently.

  • Learn how to extract the most powerful insights from your text data to support your organizational stakeholders with their vital decision-making strategies
  • A step-by-step course featuring a Python notebook build that you can reuse and adapt to solve your own real-world challenges
  • Learn how to implement key Python packages in Tensorflow 2.0
Course Length 4 hours 0 minutes
ISBN 9781789952339
Date Of Publication 30 Mar 2019


Pietro Marinelli

Pietro Marinelli has consistently been ranked among the top data scientists in the world in the Google Artificial Intelligence platform, Kaggle. He has reached 3rd position among Italian data scientists and 214th among 91,000 data scientists around the world. Due to his work on Kaggle, he has been honored to participate as a speaker in Paris Kaggle Day, January 2019. He has been working with artificial intelligence, text analytics, and many other data science techniques for many years, and has more than 10 years’ experience in designing products based on data for different industries. He has produced a variety of algorithms, ranging from predictive modeling to an advanced simulation algorithm to support senior management's business decisions for a variety of multinational companies. He is currently collaborating as a reviewer for Packt, reviewing AI books. NLP has been one of the core focuses of his projects. He has developed different algorithms for text understanding and classification in different languages (including English, Spanish, Italian, Japanese, German, French, Russian, and Chinese)