Unlocking Predictive Power: Integrating Guidewire with DataRobot for Smarter Insurance Decisions
SUMMARY: Insurance carriers integrate Guidewire InsuranceSuite (including ClaimCenter, PolicyCenter, and BillingCenter) with DataRobot, a leading enterprise AI platform, to apply advanced machine learning models directly within core workflows, enabling real-time,...
Python Using AI
SUMMARY: Python is the definitive language for Artificial Intelligence (AI) innovation because its simple, readable syntax, vast community support, and robust libraries, such as TensorFlow, PyTorch, and scikit-learn, enable users to prototype and deploy complex AI...
The Dawn of Digital Creativity: Exploring Generative AI
Introduction In the rapidly evolving landscape of artificial intelligence, one remarkable area of innovation has been the development of Generative AI (GenAI). These intelligent systems have shown their prowess in creating art, music, and even writing, raising...
Market Basket Analysis Using Snowpark Package
The term Market Basket Analysis is self-explanatory. In short, it helps find the probability of the items frequently bought together by mining the large volume of transactions for items that were often purchased together. This helps understand the customer better,...
Sentiment Analysis Using Python
What Is Sentiment Analysis? Sentiment analysis involves analyzing the opinions about a product or service expressed in the form of a text and categorizing those opinions to draw meaningful insights. Generally, these opinions are categorized into positive, negative, or...
Solving JetRail Challenge With ARIMA
The objective of JetRail Prediction hackathon is to predict passenger traffic. Using SARIMA forecasting method, we forecast passenger traffic. A typical use case of time series is predicting seasonal data. Time series is a relatively new field in data science. Popular time series libraries are Prophet from Facebook and Orbit from Uber.
Hands-on Project With Sagemaker Autopilot
Amazon Sagemaker Autopilot is used to build, train and deploy machine learning models. Sagemaker is useful for creating machine learning models without an in-depth knowledge of machine learning. It automatically evaluates the data, creates features and...
Understanding Bias and Behavior of AI Models With Sagemaker Clarify
Sagemaker Clarify is a popular tool for analyzing the intrinsic behavior of AI models. Typically it is used to explain model predictions. It is especially useful to understand the behavior of black box models and ensemble models. It is available on the AWS cloud, and integrates with other Sagemaker tools on the fly. We can invoke Sagemaker Clarify from Sagemaker notebooks.
