BOSTON, Oct. 25, 2018 (GLOBE NEWSWIRE) -- Indico founder and CTO, Slater Victoroff will be a featured speaker at the 2018 Data Science Salon Miami conference taking place November 6-7. The event brings together executives, data scientists, developers, and business development professionals from the finance and technology fields to discuss best practices, learn about innovative new solutions, and take advantage of valuable educational opportunities. This year’s event will take place at the Cambridge Innovation Center (CIC) in Miami.
Victoroff will discuss the use of text embeddings for natural language processing and how users can apply this approach for more advanced types of NLP tasks. Indico uses AI and machine learning to automate complex and expensive document-based workflows that involve the large amounts of unstructured content – text, images, video – so prevalent in enterprises today. Existing approaches to automating these types of business processes have proven inadequate to date.
Session Details:
Beyond Logistic Regression: Text Embeddings for Exotic Downstream NLP Tasks
Slater Victoroff, Founder and CTO, Indico
November 7, 2018, 9:45 – 10:15 am
The field of NLP has changed drastically in the past few years. Keyword-based approaches, ontologies, and massive taxonomies once dominated the field, but starting with the release of Google's word2vec and accentuated by the further development of sophisticated deep learning approaches, embeddings have become the de facto standard for modern NLP. Using these vectors for classification models is trivial, but most NLP tasks are not so straightforward. Come learn how to effectively set up embedding-based experiments, and specifically learn to apply embeddings to unsupervised discovery, comparison, and sequence modeling tasks.
About Indico
Indico is a provider of Enterprise AI solutions for intelligent process automation. Our focus is on helping to automate tedious back-office tasks, improving the efficiency of labor-intensive document-based workflows, and extracting valuable insights from unstructured content, including text and images. Our breakthrough in solving these challenges is an approach known as transfer learning, which allows us to train machine learning models with orders of magnitude less data than required by traditional content analysis techniques. With Indico, enterprises are now able to benefit from the dramatic advantages of machine learning in a fraction of the time. For more information, visit https://indico.io/.