- Top 5 Reasons Why Machine Learning Projects Fail - Jan 28, 2021.
The rise in machine learning project implementation is coming, as is the the number of failures, due to several implementation and maintenance challenges. The first step of closing this gap lies in understanding the reasons for the failure.
Data Preparation, Data Science, Failure, Implementation, Machine Learning
- CatalyzeX: A must-have browser extension for machine learning engineers and researchers - Jan 6, 2021.
CatalyzeX is a free browser extension that finds code implementations for ML/AI papers anywhere on the internet (Google, Arxiv, Twitter, Scholar, and other sites).
Implementation, Machine Learning, Programming, Research
- What’s the Best Data Strategy for Enterprises: Build, buy, partner or acquire? - Jul 22, 2019.
Every large organization is investing heavily in building data solutions and tools. They are building data solutions from scratch when they could be taking advantage of readily available tools and solutions. Many organizations are re-inventing the wheel and wasting resources.
Acquisitions, Enterprise, Implementation, Open Source, Strategy
- Why Data Scientists Must Know About Change Management - Feb 8, 2018.
Change management may be seen as an opposite to data science, but in reality both are related. Without proper implementation, a data science project fails.
Change Management, Data Science, Implementation
- Accelerating Algorithms: Considerations in Design, Algorithm Choice and Implementation - Dec 18, 2017.
If you are trying to make your algorithms run faster, you may want to consider reviewing some important points on design and implementation.
ActiveState, Algorithms, Implementation, Python
