• deep learning
• sentence embedding
• text classification
• chatbot
• natural language processing
• long short term memory
• neural networks

Organizations looking to increase service productivity may adopt artificial intelligence for time savings and efficiency. Developers build modern chatbots on AI technologies, including deep learning, NLP, and machine learning (ML) algorithms. This project aims to build a chatbot, using LSTM neural networks, which can recognize support requests and help the organization to solve the problem of a customer. We will discuss the tools and techniques needed to reach the final goal such as data extraction and analysis, text preprocessing, sentence embeddings, and so on. We will explain some of the most common architecture for deploying the application and make it available to the user. Finally, we introduce the concept of data drift and how to adjust the model to allow correct predictions of new problems that may occur over time.