Blog Tags: Data Science
Analytics Leadership Transformation in Response to COVID-19: Key Strategies
Discover how analytics leaders are redefining their strategies in response to COVID-19. Understand the utilization of cloud technologies, proactive business collaboration, and how to adapt to new uncertainties based on the evolving role of data science.
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Cracking the Code of Polymorphism in Organic Crystals: A Breakthrough in Pharmaceutical Research
Explore the intricate world of organic crystal polymorphism in drug development as researchers decode surface and bulk nucleation rates, unveiling the key to preventing unwanted crystallization. A breakthrough in understanding molecular packing dynamics sheds light on preventing drug failures such as Abbott Laboratory’s Norvir® recall.
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Data-Driven Disruption? How Analytics is Shifting Gears in the Auto Market
The presence of legacy systems, regulatory compliance issues and sudden growth of the BEV/PHEV market are all challenges the automotive industry must face. Explore how Analytics can help future-proof their growth plans.
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Data Science Strategies for Effective Process System Maintenance
Industry understanding of managing planned maintenance is fairly mature. This article focuses on how Data Science can impact unplanned maintenance, which demands a differentiated approach to build insight and understanding around the process and subsystems.
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Maximizing Efficiency: Redefining Predictive Maintenance in Manufacturing with Digital Twins
Tiger Analytics leverages ML-powered digital twins for predictive maintenance in manufacturing. By integrating sensor data and other inputs, we enable anomaly detection, forecasting, and operational insights. Our modular approach ensures scalability and self-sustainability, yielding cost-effective and efficient solutions.
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Enhancing Mental Healthcare: Machine Learning’s Role in Clinical Trials
Unveil the pivotal role of machine learning in revolutionizing mental health care through advanced clinical trials. Discover how innovative AI solutions, like speech analytics, enhance the evaluation of mental health treatments, contributing to more accurate and efficient healthcare outcomes.
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Strategic Guide: Maximize the Power of Bayesian Belief Networks
Examine the use of Bayesian Belief Networks for event prediction, driver analysis, and intervention assessment. Get actionable insights on the construction and practical applications of these networks in the healthcare sector – and how to enhance predictive accuracy while making data-driven decisions.
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A Beginner’s Guide: Enter the World of Bayesian Belief Networks
Get to know what makes Bayesian Belief Networks (BBNs) a powerful tool in data science with an introduction to the concepts behind BBNs, their structure, applications, and benefits. Learn how BBNs use probabilistic reasoning to model complex systems and improve decision-making processes.
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How to Implement ML Models: Azure and Jupyter for Production
Learn how to implement Machine Learning models using Azure and Jupyter for production environments – from model development to deployment, including environment setup, training, and real-time predictions. Understand the advantages of using Azure’s robust infrastructure and Jupyter’s flexible interface to streamline the entire process.
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A Brief Guide: Managing Strategic Risks with Data Science
Utilize data science to manage strategic risks in business operations through predictive analytics, risk modeling, and data-driven insights. Find out how you can support informed decision-making and enhance risk management practices with cutting-edge data science tools.
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