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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Meta AI Introduces MLGym: A New AI Framework and Benchmark for Advancing AI Research Agents

Marktechpost

The benchmark, MLGym-Bench, includes 13 open-ended tasks spanning computer vision, NLP, RL, and game theory, requiring real-world research skills. This system, the first Gym environment for ML tasks, facilitates the study of RL techniques for training AI agents.

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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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Track, allocate, and manage your generative AI cost and usage with Amazon Bedrock

AWS Machine Learning Blog

This tagging structure categorizes costs and allows assessment of usage against budgets. ListTagsForResource : Fetches the tags associated with a specific Bedrock resource, helping users understand how their resources are categorized. He focuses on Deep learning including NLP and Computer Vision domains.