Tag: Data analysis
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LinkedIn offers AI-powered tools for ad copy generation
LinkedIn introduces a new AI-powered tool that will help marketers generate multiple ad copies. This tool analyzes data from a marketer's LinkedIn page and Campaign settings to provide suggestions based on targeting criteria and objectives. The feature is currently available to users in North America and is still in its testing phase. LinkedIn aims to add more features, expand it to new regions, and support other languages shortly. The tool is expected to improve creativity and reduce the time spent on day-to-day tasks.
Save on Cost, Time, and Security with AI and Machine Learning
Discover how integrating AI/ML can benefit businesses despite the cost. Improve automation, enhance processes, and create robust security measures for your IT ecosystem. Stay ahead in today's digital world.
The Future of Retail: Machine Learning and AI Integration in EPOS Systems
Discover how the retail industry is utilizing artificial intelligence (AI) and machine learning in Electronic Point of Sale (EPOS) systems to gain insights into customer behavior, optimize pricing, and enhance operational efficiency. The integration of these technologies is revolutionizing the retail landscape and empowering retailers to thrive in the digital age.
Google Launches New Learning and Consulting Offers to Help Enterprises on Their AI Journey
Google Cloud expands its consulting services to assist customers with cloud management, providing training for executives to access AI's benefits responsibly. Google offers on-demand learning and credential programmes for a seamless cloud journey. Generative AI consulting is also introduced to automate processes and provide hands-on experience with production-bound AI solutions. Google's unique reference architectures and workflows facilitate individual and industrial use case scenarios, delivering a competitive edge in modernizing infrastructure.
Stressor: A Package for Evaluating Machine Learning Models
Discover Stressor: An R package created to help researchers determine the accuracy of predictive models quickly. The package allows R users to leverage the power of Python's PyCaret library without learning Python itself, making it easier to compare and refine machine learning models. With synthetic data set generation functions and accuracy comparison metrics, this package is a valuable tool for machine learning experts and beginners alike.