The MLOps Blog

FEBRUARY 22, 2024

TL;DR: In many machine-learning projects, the model has to frequently be retrained to adapt to changing data or to personalize it. Continual learning is a set of approaches to train machine learning models incrementally, using data samples only once as they arrive. What is continual learning?

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Unite.AI

JULY 31, 2023

This approach is known as self-supervised learning , and it’s one of the most efficient methods to build ML and AI models that have the “ common sense ” or background knowledge to solve problems that are beyond the capabilities of AI models today.

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Mlearning.ai

JULY 11, 2023

You can use libraries like TensorFlow or PyTorch to practice building simple neural networks. Step 4: Learn About Different Deep Learning Architectures Deep learning offers various architectures for specific tasks. Step 6: Apply Deep Learning to Specific Domains Deep learning is used in many areas.

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Viso.ai

MARCH 26, 2024

This enhances the interpretability of AI systems for applications in computer vision and natural language processing (NLP). The introduction of the Transformer model was a significant leap forward for the concept of attention in deep learning. Learn more by booking a demo. Vaswani et al.

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Viso.ai

DECEMBER 21, 2023

Over the past decade, the field of computer vision has experienced monumental artificial intelligence (AI) breakthroughs. This blog will introduce you to the computer vision visionaries behind these achievements. Viso Suite is the end-to-End, No-Code Computer Vision Solution.

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Viso.ai

MARCH 8, 2024

Viso Suite delivers the entire end-to-end ML pipeline, allowing teams to seamlessly implement computer vision into their workflows. To learn more, book a demo with our team. And, Generative Adversarial Networks (GANs) , which opened new doors for generating high-quality, realistic images.

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