Understanding who your most influential customers are—those who consistently recommend your business—is essential for sustainable, cost-effective growth. This approach, called social influencer analysis, identifies customers who act as connectors and referral hubs within your customer base. Historically, performing this type of analysis required complex Excel formulas or specialized ...

Turning raw latitude and longitude coordinates into meaningful addresses is a foundational step in any geospatial analysis. This article evaluates the ten best reverse geocoding APIs designed for data science workflows, comparing them on accuracy, performance, Python integration, and pricing to help you find the perfect tool for enriching your ...

ARIMA (short for AutoRegressive Integrated Moving Average) is a classic statistical model for time series forecasting. It works by combining three elements: autoregression (using past values to predict future ones), integration (removing trends to make data stationary), and moving averages (capturing patterns in forecast errors). For analysts, it’s valuable ...

Feature engineering involves transforming raw data into meaningful variables to enhance machine learning models. It includes creating new features, encoding categorical data, and scaling or normalizing values—tasks that significantly boost model accuracy and insights. This practice naturally overlaps with data cleaning, as both involve handling missing values, inconsistencies, and ...

Decision trees are intuitive analytical tools that help us explore and predict outcomes by asking simple, branching questions about our data. They’re popular because they’re visual, easy to interpret, and closely mimic human decision-making processes. However, Excel users historically faced an uphill battle using decision trees. There’s ...

Another interesting decision, now for 'Beyond Nelson-Siegel and splines: A model-agnostic Machine Learning framework for discount curve calibration, interpolation and extrapolation'

As analysts, we constantly report on KPIs and metrics critical to our businesses. That’s essential… but the numbers we present aren’t always as black-and-white as they seem. Every metric comes with uncertainty, errors, and limitations. Bootstrapping is a simple yet powerful statistical method that helps you quantify how ...

The video below shows you how to make multiple plots with Bokeh. This is a valuable tool when you are trying to develop multiple visualizations for comparison purposes.

Hierarchical clustering is a technique that groups similar data points into clusters based on their attributes, forming a hierarchy or tree-like structure. Imagine organizing customers based on their purchasing behaviors or demographics to discover distinct segments you can target differently. For business users who rely on Excel, hierarchical clustering is ...

When it comes to data science training, one size doesn’t fit all. At Jumping Rivers, we’ve built our reputation around delivering customised, expert-led training that actually fits your team’s goals, tools, and workflows - whether you’re in...