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
Delivery
- Case study + Labs using the Qu.Academy
*If you would like an invoice for your payment for reimbursement or related questions on alternative payment methods, please contact info@qusandbox.com
Who should attend?
- Model Risk professionals, Model validators, Regulators and Financial professionals new to data-driven methodologies
- Quantitative analysts, investment professionals, Machine learning enthusiasts interested in understanding model risk and governance aspects in fintech, insurance and financial organizations
Neural Networks
- Introduction to Deep Neural Networks
- Introduction to Keras and Tensorflow
- MLPs, CNNs, RNNs, Encoder Decoders
- Deep Learning techniques
- CBuilding 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
Case Studies and Frontier Topics
- 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 mode
Course instructor:
Sri Krishnamurthy, CFA
Chief Data Scientist, QuantUniversity
Sri Krishnamurthy is the founder of www.quantuniversity.com, a data and Quantitative Analysis Company and the creator of the Analytics Certificate program and Fintech Certificate program. Sri has more than two decades of experience in analytics, quantitative analysis, statistical modeling and designing large-scale applications.
Prior to starting QuantUniversity, Sri has worked at Citigroup, Endeca, MathWorks and with more than 25 customers in the financial services and energy industries. He has trained more than 1000 students in quantitative methods, analytics and big data in the industry and at Babson College, Northeastern University and Hult International Business School.
Sri earned an MS in Computer Systems Engineering and another MS in Computer Science, both from Northeastern University and an MBA with a focus on Investments from Babson College.
QuantUniversity (www.quantuniversity.com) is a quantitative analytics and machine learning advisory based in Boston, Massachusetts. QuantUniversity runs various data science and machine learning workshops in Boston, New York, Chicago, San Francisco and online. The company offers an Analytics Certificate Program and the Fintech Certificate program along with multiple workshops in its Explore-Experience-Excel series. Contact us at info@qusandbox.com
Past Attendees of QuantUniversity workshops include 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..