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Unlocking AI: Machine learning as a service

CIO

To keep pace with demand for insights that can drive quicker, better decision making, data scientists are looking to Artificial Intelligence (AI), Machine Learning (ML) and cognitive computing technologies to take analytics to the next level. Click here to read the full article from HP. [1]

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Difference between Artificial Intelligence and Machine Learning

The Crazy Programmer

In this article we are going to see the difference between two important terms in emerging computer science. We are talking about machine learning and artificial intelligence. But they aren’t the same and we will see all the differences between them in this article. Supervised learning. Future of AI.

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Machine learning for Java developers: Algorithms for machine learning

InfoWorld

Large language models like ChatGPT and Bard have raised machine learning to the status of a phenomenon. Tech companies are investing heavily in machine learning, so knowing how to train and work with models is becoming essential for developers.

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When it comes to large language models, should you build or buy?

TechCrunch

Tanmay Chopra Contributor Share on Twitter Tanmay Chopra works in machine learning at AI search startup Neeva , where he wrangles language models large and small. Last summer could only be described as an “AI summer,” especially with large language models making an explosive entrance.

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FlyteInteractive: Interactive development for machine learning models

InfoWorld

Machine learning (ML) is becoming an increasingly important part of the modern application stack. Whether it’s large-scale, public large language models (LLM) like GPT or small-scale, private models trained on company content, developers need to find ways of including those models in their code.

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Article: Testing Machine Learning: Insight and Experience from Using Simulators to Test Trained Functionality

InfoQ Culture Methods

When testing machine learning systems, we must apply existing test processes and methods differently. Machine Learning applications consist of a few lines of code, with complex networks of weighted data points that form the implementation.

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Machine learning for Java developers: Machine learning data pipelines

InfoWorld

The article, Machine learning for Java developers: Algorithms for machine learning , introduced setting up a machine learning algorithm and developing a prediction function in Java. This article picks up where that one left off. To read this article in full, please click here