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Credit Risk Modeling: Importance, Model Types, and 10 Best Practices
What Is Credit Risk Modeling? Credit risk is the likelihood that a borrower will default...
Dynamic Pricing Models: Types, Algorithms, and Best Practices
What Are Dynamic Pricing Models? Dynamic pricing models are pricing strategies that allow businesses to...
How To Make Great ML Products
Machine learning (ML) has been widely recognized as a powerful tool for solving complex problems in various industries, from retail and banking to healthcare and insurance. However, many...
What are Recommender Systems? Use Cases, Types, and Techniques
A recommender system, also known as a recommendation system, is a subclass of information filtering...
Model Drift: What Is It and How to Prevent It
Model drift refers to the change in the statistical properties of the target function that a machine learning model is trying to approximate. This can happen over time...
Data Drift: Types, Detection Methods, and Mitigation
What Is Data Drift? Machine learning models are only as good as the data they ingest during and after training. Data drift refers to a change in the...
DDC – Direct Data Connectors: Monitoring ML Models at Scale
Intro We are excited to announce Direct Data Connectors (DDC), a novel way to monitor your...
Target, Walmart, Macy’s & Kohl’s: Demand Forecasting in a Dynamic World
Demand Forecasting ML models present huge potential for retailers to generate a lot of revenue...
Machine Learning: Concepts, Algorithms, and Real-World Applications
What Is Machine Learning? Machine learning is a technological field that focuses on systems that...
Ultimate Guide to MLOps: Process, Maturity Path and Best Practices
What is Machine Learning Operations (MLOps)? Machine learning (ML) models can provide valuable insights, but...
Machine Learning Models: 4 Real Life Challenges and Solutions
What Is a Machine Learning Model? A machine learning model is a program that finds...
SHAP: Are Global Explanations Sufficient in Understanding Machine Learning Predictions?
After training a machine learning (ML) model, data scientists are usually interested in the global...