If you are in the market looking for automated machine learning (AutoML) tools, there are plenty of choices. Forrester Research recently published a report highlighting nine Automation Focussed Machine Learning Solutions and named dotData a leader. The report underscores the importance of Feature Engineering and Explainability as key differentiating factors for leaders in the AutoML space. But if you are new to machine learning or are part of a BI and analytics team with a mandate to incorporate predictive analytics, how do you decide which AutoML tool is right for you? What are some of the factors that you should consider as you make your decision? The end-user & skill set Any data science project is going to start with identifying business use cases and requirements. The process is also heavily dependent on the available resources of the business as well as the skill-set of the primary intended users. In…
A lot has been written over the past few years about AutoML. Automated Machine Learning is a rapidly growing category of software platforms in the field of data science. Looking at the world of data science strictly from the perspective of automating the machine learning component leaves a lot to be desired. In fact, the vast majority of the work that data scientists must perform is often associated with the tasks that preceded the selection and optimization of ML models. The automation of feature engineering is at the heart of data science. The infographic below shows a side-by-side comparison of how typical “AutoML” platforms can help the data scientist vs. data science automation: Made with Visme Infographic Maker OR Linked at:Infographic: data science automation vs automl Related Articles
continued from last week's post... dotData, Data Science Without The Headaches dotData is a brand new breed of AutoML product that provides what we call Full Cycle Data Science Automation. At the heart of our vision is the idea that the data science process should be fast, easy to perform, and easy to analyze and deploy, from raw business data to the business values. Our vision has led us to develop dotData Enterprise and dotData Py, two related platforms that leverage the same automation engine in uniquely different ways. dotData Enterprise is ideal for the citizen data scientist: fully automated, point-and-click driven, and ready to automate 100% of the data science process without requiring in-depth knowledge of how data science works. dotData Py, on the other hand, is ideal for data scientists. dotData Py provides a python library for Jupyter notebooks, one of the most popular data science platforms available.…
