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Continual Learning: Methods and Application

The MLOps Blog

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. These problems keep many ML practitioners awake at night.

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A Step-by-Step Guide to Learning Deep Learning

Mlearning.ai

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. Learn how to fine-tune model parameters effectively.

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SEER: A Breakthrough in Self-Supervised Computer Vision Models?

Unite.AI

In the past decade, Artificial Intelligence (AI) and Machine Learning (ML) have seen tremendous progress. Modern AI and ML models can seamlessly and accurately recognize objects in images or video files. The SEER framework allows developers to train large & complex ML models on random data with no supervision, i.e

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Unpacking the Power of Attention Mechanisms in Deep Learning

Viso.ai

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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The 11 Top AI Influencers to Watch in 2024 (Guide)

Viso.ai

From the development of sophisticated object detection algorithms to the rise of convolutional neural networks (CNNs) for image classification to innovations in facial recognition technology, applications of computer vision are transforming entire industries. We ranked these individuals in reverse chronological order.

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Midjourney vs. Stable Diffusion: Which Should You Use?

Viso.ai

About us: Viso Suite is the premier machine learning infrastructure for intelligent enterprise solutions. 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.