Predictive analytics has long been essential for making data-driven decisions. Today, deep learning offers models that can automatically find hidden patterns and trends in data—without requiring extensive manual work. However, the high cost of computation and long training times can make deep learning challenging to use for real-time forecasting.

RoadMap TrailBlazer: Simplifying Deep Learning for Forecasting

RoadMap TrailBlazer overcomes these challenges by offering a library of pre-trained deep learning models. This makes it easy for anyone to use advanced predictive analytics. Here’s how it works:

  • Easy Model Selection: Choose from a wide range of proven and new model architectures. Many users appreciate models based on @Nixtla’s NeuralForecast, which are popular in both research and real-world applications.
  • Automatic Best-Model Finding: If you’re unsure which model fits your data, select the ‘All’ option. TrailBlazer runs all available models, checks their past performance, and picks the best one—all within minutes.
  • Direct Excel Integration: After the prediction is complete, the results—including key performance details—are sent straight to an Excel sheet, making it simple to view and analyze the insights.

Improving Forecast Accuracy with Transfer Learning

To deal with the usual challenges of deep learning, such as the need for huge amounts of data and long training times, TrailBlazer uses transfer learning. This approach works in two main steps:

  1. Pre-Training on a Large Dataset: The models are first trained on the M4 dataset, a very large and diverse set of time series data.
  2. Fine-Tuning on Your Data: The pre-trained models are then adjusted to match the specific characteristics of your own data. This speeds up training and improves the accuracy of the forecasts.

In tests, our models improved predictive accuracy by 15% (measured by reduced RMSE) on datasets from both the pharmaceutical and wellness industries.

Real-World Example: Lab of Data Deep Learning Forecast

For example, in a recent demo using historical weekly sales data for wellness products, our pre-trained models successfully captured seasonal trends and produced accurate forecasts. This helps users make quicker and better decisions.

Watch the Demo
Click to watch a YouTube demo of deep learning forecasting in action!

Ongoing Innovation for Smarter Analytics

At RoadMap, we know that effective predictive analytics is an ongoing process. Our team is committed to:

  • Testing New Models: Continuously evaluating and refining deep learning architectures to keep TrailBlazer up-to-date.
  • Enhancing Custom Options: Adding more fine-tuning choices so you can adjust predictions to fit your specific business needs.
  • Broadening the Model Range: With over 40 advanced forecasting models already available, TrailBlazer turns tasks that once took weeks into processes that take just minutes.

Get Started Today!

Whether you’re an experienced data scientist or a business leader looking to improve your forecasts, RoadMap TrailBlazer provides a straightforward, powerful solution that turns raw data into clear, actionable insights.
Learn more about TrailBlazer and purchase a subscription.

Thank you for reading, and stay tuned for more updates as we continue to make deep learning for predictive analytics even more accessible!