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Machine Learning Spotlight (Part 2) – How Convolutional Neural Networks Work
In a previous blog post, we talked about Recurrent Neural Networks (RNNs), and how they are the go-to neural network architecture for Natural Language Processing (NLP) tasks. Here, we’ll follow up on this...
Classification Metrics (Part 2) – Actionable Training Tips To Improve Your Bot Dataset
You’ve built a chatbot, but it’s not performing as you’d like, and it seems like the problem is coming from the training of your dataset. Knowing where to start when you want to improve the performance of...
Classification Metrics (Part 1) – How To Boost Your Bot Performance Through Data
Today, building a bot is an easy process. There are many tools, like SAP Conversational AI, that allows you to quickly build your own AI. But accurately measuring the effectiveness of your bot can quickly turn into...
Reinforcement Learning (Part 3) – Challenges And Breakthroughs
Overview If you haven’t yet read Part 1 or Part 2 of our reinforcement learning series, you can check them out here and here. Part 1: You will learn about key concepts of reinforcement learning that will help you...
Reinforcement Learning (Part 2) – Applications And Comparisons With Other Types Of Machine Learning Algorithms
If you haven’t yet read the reinforcement learning primer go back and check it out first here. That article will provide you with the key concepts in reinforcement learning. Then you will be ready to fully compare...
Reinforcement Learning (Part 1) – The Mario Bros Example
Imagine a world where every computer system is customized specifically to your own personality. It learns the nuances of how you communicate and how you wish to be communicated with. Interacting with a computer...
How to create a Seq2Seq network in eager execution with Tensorflow
Seq2Seq is a machine learning architecture based on the encoder-decoder paradigm. It is widely used for tasks such as translation, Q&A and other cases where it is desirable to produce a sequence from another....
Text clustering using R: an introduction for data scientists
Some months ago, we talked about text clustering. From supervised to unsupervised clustering, we drew a global picture of what can be done in order to make a structure emerge out of your data. Today, we will work...
Ethically designing chatbots for the future: How to not be influenced by the past
Human Bias to Data Bias Machine Learning(ML) and Artificial Intelligence(AI) revolutionize the way software is designed. Before the ML and AI days, it was humans who needed to think through and add in every...
How Computers Understand Words: A Word Vector Primer
How on earth does my computer understand words? If you think that there is a person hiding in your computer, then we have news for you! There is not. There is however, a super complex algorithm that very smart data...