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AutoML and Beyond – Part 2

By dotData

Watch Part 2 (the Conclusion) of "AutoML and Beyond." With AutoML trending in data science, our CEO spoke at #Ai4Finance on data preparation, aggregating tables, feature engineering, the #AutoML process, and AutoML’s missing gaps.  Video: AutoML and Beyond - Part 2 Share On [social_warfare ] Related Articles

AutoML and Beyond – Part 1

By dotData

With AutoML trending in data science, our CEO spoke at #Ai4Finance on data preparation, aggregating tables, feature engineering, the #AutoML process, and AutoML’s missing gaps.  We’ll post the Conclusion / Part 2 next Thursday.  Video: Part 1 – AutoML and Beyond. Share On [social_warfare ] Related Articles

Ai4 Finance: dotData CEO Promotes Automated Feature Engineering

By dotData

We are proud to share a few photos from the #Ai4Finance2019 New York Conference.  With such a great turnout, our founder and CEO Ryohei Fujimaki displayed many of the new #datascience #innovations where dotData is paving the way for #AutomatedFeatureEngineering. Related Articles

Automated Machine Learning vs. Data Science Automation [Infographic]

By dotData

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

How Will Automation Change Enterprise Data Science? – Part 2

By dotData

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.…

How Will Automation Change Enterprise Data Science? – Part 1

By dotData

According to a recent study by Dimensional Research, Over 96% of enterprise companies struggle with AI and Machine Learning (ML) projects. The reasons behind the incredibly high failure rates are numerous, but many are associated with shortages of staff, data that requires too much pre-processing to use appropriately, and a lack of understanding of the ML models on the part of business users. Organizations struggle with AI and machine learning, in large part, because projects take too long to complete, lab-generated results are often difficult to recreate in production environments, and the value derived by AI and ML projects is not clear enough.  AI & Machine Learning Automation - The Solution To All Our Problems? Recently, several startups have come to market with innovative platforms designed to "automate" the process of generating machine learning models. The promise of "AutoML" as it has become known, is that by accelerating the machine-learning…

Ryohei Fujimaki at PAWCon 2019

By dotData

Ryohei Fujimaki, PhD and CEO of dotData, shares more about the data science platform at Predictive Analytics World 2019 in Las Vegas.https://twitter.com/thebloorgroup/status/1141688670421954560 Related Articles

Come see us at Predictive Analytics World 2019!

By dotData

dotData is excited to be the diamond sponsor for this year’s Predictive Analytics World exhibition at Caesars Palace in Las Vegas, NV, June 16 to the 20th. This year promises to be an exciting show with over 1,000 attendees expected and a ton of informative sessions and exhibitors.   We are also thrilled to announce that our CEO, Ryohei Fujimaki, will be speaking at 9:40AM in the Octavious ballroom on how automation is poised to change data science. Don’t forget to stop by and see us at booth 502, to see the exciting innovations that we will be discussing for both our Enterprise dotData platform, as well as our dotData Py, our Python interface-based platform designed specifically for data scientists. Speaking of dotData Py, Aaron Cheng, our Vice President of Data Science and Solutions, will be hosting a “lunch and learn” session in Octavius rooms 13 & 14 at 12:20PM…

2019: The Year of AI and Machine Learning

By dotData

2018 will be remembered, in many ways, as the year that disruptive emerging technologies began to reshape business models and change the economics of organizations. According to Gartner, digital business reached a tipping point last year, with forty-nine percent of CIOs reporting that their enterprises have already changed their business models, or are in the process of doing so. When CIOs and IT leaders were asked which technologies they expect to be most disruptive, artificial intelligence (AI) was the top-mentioned technology, with data and analytics taking second place. Based on my work leading more than 100 data analysis projects across a variety of industries, the combination of these technologies is hardly surprising; it’s an accurate reflection of what my colleagues and I see in data science on a daily basis. Data science is now a major area of technology investment for organizations, driven by the impact it can have on…