Meet explainX.ai - an xAI system that helps data scientists understand, explain and validate any machine learning algorithm. The main aim is to help business increase transparency into 'black-box' AI models, remove biases and build trust into AI predictions.
explainX.ai can be easily used by a data scientist in their Jupyter Notebook in a single line of code.
Right now, most of the machine learning models are black-boxes which means we do not know how and why they work. Due to this, around 85% of the models built by data scientists are never used and fail to provide any business value. We discovered that the main reason behind was high amount of skepticism about AI predictions from the business managers side - business managers do not trust what they do not understand.
Lorem Ipsum has been the industry's standard dummy text ever since the 1500s, when an unknown printer took a galley of type and scrambled it to make a type specimen book.
Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry's standard dummy text ever since the 1500s, when an unknown printer took a galley of type and scrambled it to make a type specimen book.
Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry's standard dummy text ever since the 1500s, when an unknown printer took a galley of type and scrambled it to make a type specimen book.
Lorem Ipsum is simply dummy text of the printing and typesetting industry.
Lorem Ipsum is simply dummy text of the printing and typesetting industry.