Remove Categorization Remove Computer Vision Remove NLP
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10 Best AI Tools to Protect Your Brand and Streamline Influencer Marketing (December 2024)

Unite.AI

These innovative platforms combine advanced AI and natural language processing (NLP) with practical features to help brands succeed in digital marketing, offering everything from real-time safety monitoring to sophisticated creator verification systems.

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20 GitHub Repositories to Master Natural Language Processing (NLP)

Marktechpost

Natural Language Processing (NLP) is a rapidly growing field that deals with the interaction between computers and human language. As NLP continues to advance, there is a growing need for skilled professionals to develop innovative solutions for various applications, such as chatbots, sentiment analysis, and machine translation.

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Supervised vs Unsupervised Learning for Computer Vision (2024 Guide)

Viso.ai

In the field of computer vision, supervised learning and unsupervised learning are two of the most important concepts. In this guide, we will explore the differences and when to use supervised or unsupervised learning for computer vision tasks. We will also discuss which approach is best for specific applications.

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Five machine learning types to know

IBM Journey to AI blog

Machine learning (ML) technologies can drive decision-making in virtually all industries, from healthcare to human resources to finance and in myriad use cases, like computer vision , large language models (LLMs), speech recognition, self-driving cars and more. However, the growing influence of ML isn’t without complications.

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Conversational AI use cases for enterprises

IBM Journey to AI blog

Beyond the simplistic chat bubble of conversational AI lies a complex blend of technologies, with natural language processing (NLP) taking center stage. NLP translates the user’s words into machine actions, enabling machines to understand and respond to customer inquiries accurately. What makes a good AI conversationalist?

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Making Sense of the Mess: LLMs Role in Unstructured Data Extraction

Unite.AI

This advancement has spurred the commercial use of generative AI in natural language processing (NLP) and computer vision, enabling automated and intelligent data extraction. Named Entity Recognition ( NER) Named entity recognition (NER), an NLP technique, identifies and categorizes key information in text.

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Huawei Researchers Introduce a Novel and Adaptively Adjustable Loss Function for Weak-to-Strong Supervision

Marktechpost

In computer vision, convolutional networks acquire a semantic understanding of images through extensive labeling provided by experts, such as delineating object boundaries in datasets like COCO or categorizing images in ImageNet.