Demystifying Natural Language Processing across Several Industry Verticals

Oct 23 5:44 PM CDT :calendar:
Audience level: Intermediate

About This Talk

Natural Language Processing (NLP) is the ability of a machine to understand human language. NLP is a popular field of data science and is widely used across different industry verticals to solve for various challenges. This talk will highlight NLP, what it is and will follow into how over 5 industries use NLP to solve for their use cases. The industries include e-commerce, finance, real estate, social media, and more. This talk will then progress into some practical implementations of the common industrial solutions that are widely used across the globe today. These applications include sentiment analysis, automated customer service solutions like chatbots, and more. Furthermore, using open-source libraries to build these NLP utilizations will be discussed and presented.


    Photo of Jyotika Singh

    Jyotika Singh

    Jyotika Singh is the VP of Data Science at ICX Media, where she manages and mentors her team as they research on NLP, feature engineering, machine learning, data analytics, distributed computing, social media data and audiences data using Python, Spark, and GCP. She is an inventor of multiple patents on data science, classification and reclassification algorithms, processes and optimizations for media and audience marketing campaigns. Her efforts in driving data science and analytics at ICX along with introduction of new methods and processes have strongly contributed to reducing operating costs, securing new clients and achieving high double digit revenue growth in the past year with positive EBITDA.

    She earned her Bachelor’s in Engineering Hons. in Electronics and Communications Engineering from Birla Institute of Technology and Science, Pilani, Dubai (BITS) where she published multiple papers on her research in Signal Processing and Communications and earned a silver medal for the entire graduating class of 2014 and 1st rank for the Electrical Engineering class of 2014. She then earned her Master’s in Science from the University of California, Los Angeles (UCLA) where she researched on signal and speech processing, developed novel approaches to remove noise from speech and worked on a variety of machine learning projects on image, text, user ratings, social media, entertainment and movies data. Outside her work, she enjoys working on a variety of problem solving techniques on text, audio and image data. She has opened multiple github open source projects, such as pyAudioProcessing, and has been a speaker at multiple conferences across the globe to share her findings and work with the Python and Data Science community.

    She is passionate about encouraging women in STEM and continues mentorship efforts to support the topic. She volunteers as a Data Science Mentor at Data Science Nigeria and Women Impact Tech.