John Snow Labs NLU: The simplicity of Python, the power of Spark NLP

October 7th at 1:45 PM ET – 2:15 PM ET

Register – Free

Learn how to unleash the power of 350+ pre-trained NLP models, 100+ Word Embeddings, 50+ Sentence Embeddings, and 50+ Classifiers in 46 languages with 1 line of Python code.

John Snow Labs’ new NLU library marries the power of Spark NLP with the simplicity of Python. Tackle NLP tasks like NER, POS, Emotion Analysis, Keyword extraction, Question answering, Sarcasm Detection, Document classification using state-of-the-art techniques.

The end-to-end library includes word & sentence embeddings like BERT, ELMO, ALBERT, XLNET, ELECTRA, USE, Small-BERT, and others; text wrangling and cleaning like tokenization, chunking, lemmatizing, stemming, normalizing, spell-checking, and matchers; and easy visualization capabilities using your embedded data with T-SNE.

Christian Kasim Loan, the creator of NLU, will walkthrough NLU and show you how easy it is to generate T-SNE visualizations of 6 Deep Learning Embeddings, achieve top classification results on text problems from Kaggle competition with 1 line of NLU code, and leverage the latest & greatest advances in Deep Learning & Transfer Learning.

About the speaker
Christian Kasim Loan

Christian Kasim Loan

Senior Data Scientist at John Snow Labs

Christian Kasim Loan, also known as CKL is a computer scientist with over 10 years of coding experience who works for John Snow Labs as a Senior Data Scientist where he helps porting the latest and greatest Machine Learning Models to Spark and created the NLU library. 

In the past, he architected and implemented a real-time big data lambda architecture for a Daimler research lab in Azure with Kubernetes, Prometheus Grafana, and Kafka. The created system is able to process millions of car generated IoT data streams in parallel, perform Geo-Spatial and Temporal analytics like traffic flow prediction with Graph Neural Networks on it, and visualize the results all in real-time and automatically scalable and built-in a self-healing fashion.

Before working at a Daimler lab, CKL worked at various AI labs in Berlin like GT-ARC and the Distributed Artificial Intelligence (DAI) where he built the big data infrastructure for the Meta Machine learning project CODA. In cooperation with DAI and Deutsche Telekom, CKL also created two NLP chatbots, one that consults customers on which mobile phone to buy and a second one that consults customers on what mobile phones to buy.CKL also created and manages the CKL-IT consulting company, which works on various projects in the Big Data, DevOps, Data Science, Mobile-App, and Web domains.


Sessions: October 6 – 9
Trainings: October 13 – 16


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