A prediction from a machine learning perspective is a single point that hides the uncertainty of that prediction. Prediction intervals provide a way to quantify and communicate the uncertainty in a prediction. They are different from confidence intervals that instead seek to quantify the uncertainty in a population parameter such as a mean or standard […]
Sequence prediction is different from other types of supervised learning problems. The sequence imposes an order on the observations that must be preserved when training models and making predictions. Generally, prediction problems that involve sequence data are referred to as sequence prediction problems, although there are a suite of problems that differ based on the […]
A powerful feature of Long Short-Term Memory (LSTM) recurrent neural networks is that they can remember observations over long sequence intervals. This can be demonstrated by contriving a simple sequence echo problem where the entire input sequence or partial contiguous blocks of the input sequence are echoed as an output sequence. Developing LSTM recurrent neural […]
Time series forecasting is a process, and the only way to get good forecasts is to practice this process. In this tutorial, you will discover how to forecast the monthly sales of French champagne with Python. Working through this tutorial will provide you with a framework for the steps and the tools for working through […]
Time series forecasting is a process, and the only way to get good forecasts is to practice this process. In this tutorial, you will discover how to forecast the annual water usage in Baltimore with Python. Working through this tutorial will provide you with a framework for the steps and the tools for working through […]
Time series forecasting is a process, and the only way to get good forecasts is to practice this process. In this tutorial, you will discover how to forecast the number of monthly armed robberies in Boston with Python. Working through this tutorial will provide you with a framework for the steps and the tools for […]
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Time series prediction problems are a difficult type of predictive modeling problem. Unlike regression predictive modeling, time series also adds the complexity of a sequence dependence among the input variables. A powerful type of neural network designed to handle sequence dependence is called a recurrent neural network. The Long Short-Term Memory network or LSTM network […]
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Any book on machine learning will list and describe dozens of machine learning algorithms. Once you start using tools and libraries you will discover dozens more. This can really wear you down, if you think you need to know about every possible algorithm out there. A simple trick to tackle this feeling and take some […]
