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 Keeping Data Under (Your) Control with Apache Airflow

Keeping Data Under (Your) Control with Apache Airflow

  • Posted by Daitan Innovation Team
  • On January 28, 2022
  • Apache Airflow, Data, Data Science, Kubernetes, Machine Learning
Clients are demanding more and more insights based on their data, but to achieve that, some foundational resources need to be in place to allow more advanced analysis and techniques. There are lots of tools and disciplines related to data handling in all aspects, both on premise and as cloud services, but we see that our clients value keeping a certain level of ownership over the entire process. In this context, Apache Airflow pops up as a good candidate for addressing this business need.
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 Efficient Distributed Training in Deep Learning

Efficient Distributed Training in Deep Learning

  • Posted by Daitan Innovation Team
  • On January 21, 2022
  • Deep Learning, DevOps, Machine Learning
At the heart of any deep learning system, there is a significant effort in building it. In the last few years, scaling deep learning models has become one of the most promising paths for artificial intelligence, specifically for large AI laboratories like OpenAI and DeepMind. To have a clear feeling of this trend, let us examine recent large language models (LLMs) such as BERT and GPT-3.
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 Machine Learning for 5G Technology, a Case Study

Machine Learning for 5G Technology, a Case Study

  • Posted by Daitan Innovation Team
  • On November 13, 2021
  • 5G, Machine Learning, Telecommunications
Identifying signal modulation types using deep convolutional neural networks. In this article, we will look at how the NG-RAN can use an end-to-end deep learning system to recognize and classify modulated RF signals and adjust channel parameters appropriately, so both ends of the communication achieve optimal, effective resource usage.
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 Why The Discovery Phase Is Essential For All Software Development Projects

Why The Discovery Phase Is Essential For All Software Development Projects

  • Posted by GM, Digital Solutions
  • On August 26, 2021
  • AI, Artificial Intelligence, Business Outcome, Discovery., Experience Design, Machine Learning, Machine Learning Project, Project Risk, Software Development, Software Projects
The Discovery Phase is paramount with all software product development. Discovery serves an important purpose by ensuring product teams learn all they can about their customers and define the optimum path to achieving the vision. They also bring stakeholders together from across the organization to align on a project’s scope and keep people focused on […]
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 5 Early Signs That Your AI Project May Fail

5 Early Signs That Your AI Project May Fail

  • Posted by GM, Digital Solutions
  • On August 5, 2021
  • AI, Artificial Intelligence, Data Science, Machine Learning, Machine Learning Project
Artificial intelligence (AI) can be a gamechanger for companies that know how to harness its full potential. Technology has the power to completely transform operations and free humans up from repetitive, mundane tasks that detract from truly exciting work. So why is there so much uncertainty surrounding AI project risk? The problem is that enterprise […]
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 Do You Have Good Data? 3 Tests To Determine The Answer

Do You Have Good Data? 3 Tests To Determine The Answer

  • Posted by GM, Digital Solutions
  • On August 3, 2021
  • Artificial Intelligence, Compliance, Data, Machine Learning, Results
Data is absolutely essential when it comes to measuring the progress of AI projects. Without trustworthy data, we don’t know whether we’re hitting key milestones or tracking towards our goals. We lose sight of how our investments are supposed to add value to the business and result in throwing money aimlessly at different problems.  Good […]
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 A Short Discussion on Bias in Machine Learning

A Short Discussion on Bias in Machine Learning

  • Posted by Daitan Innovation Team
  • On June 8, 2021
  • Artificial Intelligence, Bias, Machine Learning
Machine learning systems are being used to decide if someone should receive loans from a bank, send people to jail, or determine the optimal locations where extra police force should be sent. Though many people see these late advances as a good thing (and in fact, they could be), there is a problem that can easily outweigh the possible benefits of each of these solutions. A problem that relates to our deepest social issues and can show up on pretty much any stage of a machine learning project lifecycle.That is the problem of bias.
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 Introducing MLOps

Introducing MLOps

  • Posted by Daitan Innovation Team
  • On May 14, 2021
  • AI, Machine Learning, MLOps
An introductory discussion about MLOps and a set of essential practices for scaling Machine Learning-powered applications.
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 Three Ways Financial Services Leaders Can Create Value With AI Today

Three Ways Financial Services Leaders Can Create Value With AI Today

  • Posted by GM, Digital Solutions
  • On May 14, 2021
  • AI, Financial Services, Machine Learning
AI is transforming nearly every industry in the world. One sector, in particular, that is experiencing significant change is the financial services industry. Financial institutions (FIs) everywhere are using AI/ML to provide differentiated experiences in a market that is only growing more competitive.   Those that harness the full potential of AI/ML will survive in our […]
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 Using Data-Driven Decision-Making to Drive Business Growth

Using Data-Driven Decision-Making to Drive Business Growth

  • Posted by GM, Digital Solutions
  • On April 1, 2021
  • Artificial Intelligence, Business Goals, Data, Data-Driven, Digital Business, Machine Learning
The data you’ve collected, processed, and analyzed is no longer just data - it’s now a decision-making asset that can drive business growth.
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