by smartlake | Sep 19, 2020 | Blog, Machine Learning
Customer churn 2 Years ago I published a series of articles on LinkedIn related to customer churn ( this is part I https://www.linkedin.com/pulse/machine-learning-predict-customer-churn-accuracy-patrick-rotzetter/). I tested a few approaches and showed how to explain...
by smartlake | Apr 18, 2020 | Artificial Intelligence, banking, Blog, chatbot, Machine Learning, NLP, wealth management
Building Blocks In the first part of the series we have shown how to define intents and capture dialog attributes using AWS Lex and AWS Lamda functions (https://smartlake.ch/onboarding-virtual-assistant-for-banking-behind-the-scene-part-i/). We will dive now a little...
by smartlake | Apr 11, 2020 | Artificial Intelligence, banking, Blog, chatbot, Machine Learning, NLP, wealth management
Building Blocks In a previous article,https://smartlake.ch/onboarding-virtual-assistant-for-banking-adding-product-recommendations/, we have shown the integration of product recommendation in a simple onboarding dialogue. In this article we are going to show how we...
by smartlake | Mar 22, 2020 | Artificial Intelligence, Blog, Machine Learning, NLP, text mining
Introduction In the previous 6 articles we have illustrated the usage of Google and AWS NLP APIs. We have also experimented the spacy library to extract entities and nouns from different documents. We have shown how to improve the model using pattern matching function...
by smartlake | Jan 1, 2020 | banking, Blog, Machine Learning
Background All financial services providers need more personalized offerings when interacting with clients and especially new clients. As a client I want to get some personalized recommendations on what to do next or which product to choose. Banks and other providers...
by smartlake | Dec 27, 2019 | Artificial Intelligence, Blog, Machine Learning, NLP, text mining
Introduction In the previous 5 articles we have illustrated the usage of Google and AWS NLP APIs. We have also experimented the spacy library to extract entities and nouns from different documents. We have shown how to improve the model using pattern matching function...