Machine Learning Archives - Tiger Analytics

Blog Tags: Machine Learning

Invisible Threats, Visible Solutions: Integrating AWS Macie and Tiger Data Fabric for Ultimate Security

Data defenses are now fortified against potential breaches with the Tiger Data Fabric-AWS Macie integration, automating sensitive data discovery, evaluation, and protection in the data pipeline for enhanced security. Explore how to integrate AWS Macie into a data fabric.

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.

Defining Financial Ethics: Transparency and Fairness in Financial Institutions’ use of AI and ML

While time, cost, and efficiency have seen drastic improvement thanks to AI/ML, concerns over transparency, accountability, and inclusivity prevail. This article provides important insight into how financial institutions can maintain a sense of clarity and inclusiveness.

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.

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.

Credit Monitoring for SMEs: ML-Driven Early Warning Solutions

Explore how machine learning elevates credit monitoring for SMEs and corporations. Delve into the use of ML models for early warning solutions, enhancing risk assessment, default prediction, and financial stability in the banking sector.

REST API with AWS SageMaker: Deploying Custom Machine Learning Models

Learn how to deploy custom Machine Learning (ML) models using AWS SageMaker and REST API. Understand the steps involved, including setting up the environment, training models, and creating endpoints for real-time predictions, as well as why to integrate ML models with REST APIs for scalable deployment.

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.

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.

Detecting Unknown Defects: Leveraging GANs in Product Quality

Implement Generative Adversarial Networks (GANs) to identify hidden defects in products with details on how GANs enhance quality control by simulating defect scenarios and improving detection accuracy. Know how to transform product quality assurance with advanced AI techniques.

Blog Tags: Machine Learning

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