Interest in Neural networks is growing with many areas from image recognition to speech processing reporting impressive results. Applications in Natural language processing with Neural networks have found multiple applications. With advances in software and hardware technologies, and interest in AI based applications growing, it is time to understand neural networks applied to natural language processing better!

In this workshop, we will discuss the basics of neural networks and natural language processing and discuss how neural approaches differ from traditional natural language modelling techniques with practical applications.All participants will get a trial access to QuSandbox

What you will learn

  • Key NLP techniques
  • Key Neural Network models and techniques
  • How do you choose an algorithm for a specific goal?
  • Text tokenization, word embeddings (word2vec, Glove).
  • Deep Neural techniques and using RNNs and Encoder-Decoder networks for text processing.
  • Encoder-Decoder Seq2Seq, Seq2Vec models
  • Practical Case studies with fully functional code
Eventbrite - Machine Learning for Finance: New York and Online

Course summary


Module 1

Basics of NLP

What you will learn

  • Natural Language Processing Basics
  • Key challenges when processing text
  • Syntax and Semantics
  • Text pre-processing: Tokenization, Lemmatization, Stemming
  • Language Modeling
  • N-Grams, Bag-of-words, Word embeddings; Word2vec, Glove
  • Case study 1: Working with Edgar data in Python


Module 2

Neural Networks

What you will learn

  • Introduction to Deep Neural Networks
  • Introduction to Keras and Tensorflow
  • MLPs, CNNs, RNNs, Encoder Decoders
  • Deep Learning techniques
  • Building a Deep Neural Network with pre-trained word embeddings
  • RNNs for translation, sentiment detection and other text applications
  • Case study 2: Neural Networks for NLP Lab


Module 3

NLP applications

What you will learn

  • Designing NLP Applications
  • Data scraping and acquisition: Edgar, StockTwits, Twitter
  • Text Summarisation
  • Conversational agents-Chatbots
  • Sentiment analysis
  • Document Classification
  • Case study 3: Illustrations on various NLP techniques using Python


Module 4

Case studies and frontier topics

What you will learn

  • Pipelines for NLP: Data ingestion, pre-processing, feature extraction, model selection and deployment
  • Frontier topics
  • The future of text applications
  • Developing applications with QuSandbox
  • Case study 1: Sentiment analysis in Keras
  • Case study 2: Text Summarization using Encoder-Decoder models

Download Brochure

Sample Content from a prior workshop

Example 1

Example 2

Past QuantUniversity Workshop Attendees

Assette, Baruch College, Bentley College, Bloomberg, BNY Mellon, Boston University, Datacamp, Fidelity, Ford, Goldman Sachs, IBM, J.P. Morgan Chase, MathWorks, Matrix IFS, MIT Lincoln Labs, Morgan Stanley, Nataxis Global, Northeastern University, NYU, Pan Agora, Philips Health, Stevens Institute, T.D. Securities and many more..

Recent Courses

Coming soon again in 2018

Chicago and OnlineMay 30th and 31st

Deep Learning Workshop

QuantUniversity's Deep Learning Workshop provides the foundation to understand the core techniques in Deep Learning.

This is a hands-on course with examples in Python, Keras, TensorFlow and Spark

This workshop will be delivered in Chicago and Online by Dr.Victor Shnayder and Sri Krishnamurthy

New York & OnlineJune 8th, 9th

Machine Learning Workshop

QuantUniversity's 2-day Machine Learning Workshop provides the core Data science and machine learning techniques and applications in finance.We will also discuss the role of Big data and Deep Learning

This is a hands-on course with examples in R, Python and Spark

This workshop will be delivered in New York and online by Sri Krishnamurthy

Boston & OnlineJune 19th,20th

Anomaly Detection Workshop

QuantUniversity's 2-day Anomaly Detection Workshop provides the core techniques and best practices in Anomaly Detection and Outlier Analysis with cross-sectional and time series data.

This is a hands-on course with examples in R, Python and Spark

This workshop will be delivered in Boston and Online by Sri Krishnamurthy

Back to top