In 2017, the Robotic Process Automation / RPA market has matured. Learning from the evolution of RPA, in this post, we explore the wider implications… Read More »Enterprise AI: Learning from the evolution of Robotic Process Automaton
This article comes from Rylan Schaeffer Github. I’ve found that the overwhelming majority of online information on artificial intelligence research falls into one of two… Read More »One-shot Learning with Memory-Augmented Neural Networks
Technology has remarkably changed the way we live today, there is no denial to it. Compared with our ancestors, we stand far away from them… Read More »Technology Trends That Will Dominate 2017: Big Data, IoT, AWS and AI
Introduction Deep Learning can be used to automate just about every repetitive task that is currently or formerly performed by humans. Factory robots, autonomous cars,… Read More »Natural Language Understanding – Application Notes with Context Discriminant
Summary: If you are mid-career and thinking about switching into data science here are some things to think about in planning your journey. We get… Read More »Some Thoughts on Mid-Career Switching Into Data Science
Big Data, Data Analytics, Data Science – all these terms make a noise in the world! Here are a few examples to clarify the difference… Read More »Big Data Analytics & Data Science Use Cases
This article was written by Tim O’Reilly. Source for picture: The Onion There are many signals of likely truth or falsity that can be verified algorithmically… Read More »How I Detect Fake News
Principal Component Analysis (PCA) is a technique used to find the core components that underlie different variables. It comes in very useful whenever doubts arise about… Read More »Naive Principal Component Analysis in R
In this post, you discovered how to train a final machine learning model for operational use. You have overcome obstacles to finalizing your model, such… Read More »How to Train a Final Machine Learning Model
Cross-validation is a technique used to assess the accuracy of a predictive model, based on training set data. It splits the training sets into test… Read More »14 Great Articles About Cross-Validation, Model Fitting and Selection
