Category: Data Science

Author: Stephanie Glen Hundreds of programming languages dominate the data science and statistics market: Python, R, SAS and SQL are standouts. If you’re looking to […] Read More

Author: mtdearing HDBSCAN is a robust clustering algorithm that is very useful for data exploration, and this comprehensive introduction provides an overview of its fundamental […] Read More

Author: Bill Schmarzo I am a believer that the pathway to innovation must end with putting a product or service into the market that provides […] Read More

Author: Gregory PS Editor The cost of obtaining a MSc in #DataScience in Europe; 30 Python Best Practices, Tips, And Tricks; OpenAI is Adopting PyTorch; […] Read More

Author: Matt Mayo Editor To help practitioners make the most of recent and disruptive breakthroughs in debugging, explainability, fairness, and interpretability techniques for machine learning […] Read More

Author: mtdearing What makes deploying a machine learning project so difficult? Is it the expectations? The people? The tech? There are common threads to these […] Read More

Author: William Vorhies Summary:  Can all AI strategies be defined by a few common needs or are the different AI strategy models sufficiently unique that […] Read More

Author: /u/vogt4nick r/datascience has grown considerably in the past year, from about 70k subscribers in Jan 2019 to 183k subscribers today in Jan 2020. As […] Read More

Author: Max Frolov How to build a project from scratch by using a latest, state-of-the-art AI technology stack? After spending a few years working on […] Read More

Author: Asel Mendis While the validation process cannot directly find what is wrong, the process can show us sometimes that there is a problem with […] Read More