Comparing different types of AI/ML Partners

Comparing different types of AI/ML Partners

  • Posted by GM, Digital Solutions
  • On December 3, 2020
  • AI, Data Science, Hiring, Software Development
An AI/ML project is often more challenging than an “ordinary” software project. It comes with unique risks that can threaten the desired business outcome. Given the high rate of project failures, or those that remain in “POC Purgatory” unable to be scaled into production, it’s critical for AI project owners to understand the risks they face to reach a successful product execution. In this article we will discuss one of these risks: the importance of building a team with the right skill sets
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 Build an AI Project Team with the Right Skill Sets to Avoid Risk of Failure

Build an AI Project Team with the Right Skill Sets to Avoid Risk of Failure

  • Posted by GM, Digital Solutions
  • On November 2, 2020
  • AI, Data Science, Hiring, Software Development
An AI/ML project is often more challenging than an “ordinary” software project. It comes with unique risks that can threaten the desired business outcome. Given the high rate of project failures, or those that remain in “POC Purgatory” unable to be scaled into production, it’s critical for AI project owners to understand the risks they face to reach a successful product execution. In this article we will discuss one of these risks: the importance of building a team with the right skill sets
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 Privacy-Preserving Data Sharing for Data Science

Privacy-Preserving Data Sharing for Data Science

  • Posted by Daitan Innovation Team
  • On April 15, 2020
  • Artificial Intelligence, Data, Data Science, Data Sharing, Deep Learning, Differential Privacy, Privacy
In the last 2 decades, with the increasing availability of sensors and the popularity of the internet, data has never been so ubiquitous. Yet, having access to personal data to perform statistical analysis is hard. In fact, that is one of the main reasons we, as data analysts, spend so much time doing research using “toy” datasets, instead of using real-world data.
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 The Fundamental Tool That Data Scientists Can’t Miss

The Fundamental Tool That Data Scientists Can’t Miss

  • Posted by Daitan Innovation Team
  • On December 20, 2019
  • Convex Optimization, Data Science, Deep Learning
How business requirements can prevent you from using available Machine Learning tools and what to do about it. -- When hearing the term Convex Optimization, most people will immediately start talking about how gradient descent is the most awesome thing there is, how we can add momentum to it, how can we choose, adapt, or even circumvent the choice of the step-size parameter, and so on. However, in reality, convex optimization goes well beyond gradient descent and its variants.
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 Programming With Data

Programming With Data

  • Posted by Daitan CTO
  • On November 5, 2019
  • Data, Data Centers, Data Science, Machine Learning
In this post, I will share a very basic view of the technologies that are used to build ML solutions with the goal of helping those who have not had exposure to this domain understand where all the hype comes from. For my engineering colleagues, keep in mind that this article is meant to very simply present this technically complex field; and, does not tackle detailed technical challenges, the compelling issue of bias, and social concerns about ML/AI replacing jobs.
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 Data Science Needs More Than Scientists—It Takes a Team

Data Science Needs More Than Scientists—It Takes a Team

  • Posted by Marketing Daitan
  • On June 11, 2018
  • Agile, Data Engineer, Data Science, DevOps
Data Science projects are complex and usually result in producing pivotal technology tied to a company’s strategic growth. So, when we build a team, we start with foundational skills like Software Development, Data Engineering and (of course) Data Scientists; and we add DevOps Engineering and Quality Engineering—to ensure the net result is a product the company can use.
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 How Does High Demand for Data Science and Advanced Analytics Skills Create Business Risk?

How Does High Demand for Data Science and Advanced Analytics Skills Create Business Risk?

  • Posted by Marketing Daitan
  • On March 11, 2018
  • Analytics, Business Outcome, Data Science, Hiring
BLOG - Data Scientist is the top job in the USA. And this is the case for a few years in a row according to Glassdoor’s annual report. Demand continues to outpace available resources. A quick search of LinkedIn shows over 11.5K open Data Scientist roles and over 7.4K Data Engineering roles in the USA alone. Incredible.
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