Articles About Machine Learning

How to Save Your Machine Learning Model and Make Predictions in Weka

Last Updated on December 11, 2019 After you have found a well performing machine learning model and tuned it, you must finalize your model so that you can make predictions on new data. In this post you will discover how to finalize your machine learning model, save it to file and load it later in order to make predictions on new data. After reading this post you will know: How to train a final version of your machine learning model […]

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Text Generation With LSTM Recurrent Neural Networks in Python with Keras

Last Updated on September 3, 2020 Recurrent neural networks can also be used as generative models. This means that in addition to being used for predictive models (making predictions) they can learn the sequences of a problem and then generate entirely new plausible sequences for the problem domain. Generative models like this are useful not only to study how well a model has learned a problem, but to learn more about the problem domain itself. In this post you will […]

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How To Work Through a Multi-Class Classification Project in Weka

Last Updated on August 22, 2019 The Weka machine learning workbench is so easy to use that working through a machine learning project can be a lot of fun. In this post you will complete your first machine learning project using Weka, end-to-end. This gentle introduction to working through a project will tie together the key steps you need to complete when working through machine learning project in Weka. After completing this project, you will know: How to analyze a […]

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How To Work Through a Binary Classification Project in Weka Step-By-Step

Last Updated on December 11, 2019 The fastest way to get good at applied machine learning is to practice on end-to-end projects. In this post you will discover how to work through a binary classification problem in Weka, end-to-end. After reading this post you will know: How to load a dataset and analyze the loaded data. How to create multiple different transformed views of the data and evaluate a suite of algorithms on each. How to finalize and present the […]

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How to Grid Search Hyperparameters for Deep Learning Models in Python With Keras

Last Updated on August 27, 2020 Hyperparameter optimization is a big part of deep learning. The reason is that neural networks are notoriously difficult to configure and there are a lot of parameters that need to be set. On top of that, individual models can be very slow to train. In this post you will discover how you can use the grid search capability from the scikit-learn python machine learning library to tune the hyperparameters of Keras deep learning models. After […]

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How to Work Through a Regression Machine Learning Project in Weka

Last Updated on August 22, 2019 The fastest way to get good at applied machine learning is to practice on end-to-end projects. In this post you will discover how to work through a regression problem in Weka, end-to-end. After reading this post you will know: How to load and analyze a regression dataset in Weka. How to create multiple different transformed views of the data and evaluate a suite of algorithms on each. How to finalize and present the results […]

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5 Step Life-Cycle for Neural Network Models in Keras

Last Updated on August 27, 2020 Deep learning neural networks are very easy to create and evaluate in Python with Keras, but you must follow a strict model life-cycle. In this post you will discover the step-by-step life-cycle for creating, training and evaluating deep learning neural networks in Keras and how to make predictions with a trained model. After reading this post you will know: How to define, compile, fit and evaluate a deep learning neural network in Keras. How […]

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How to Get More Help For the Weka Machine Learning Workbench

Last Updated on August 15, 2020 The Weka machine learning workbench is an easy to use and powerful platform for applied machine learning. Even though it is easy to use, you may still require some help or advice when using it on your own problems. In this post you will discover resources that you can use to get more help with Weka. After reading this post you will know: About the documentation that is installed with Weka on your workstation. […]

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Weka Machine Learning Mini-Course

Last Updated on August 22, 2019 Become A Machine Learning Practitioner in 14-Days Machine learning is a fascinating study, but how do you actually use it on your own problems? You may be confused as to how best prepare your data for machine learning, which algorithms to use or how to choose one model over another. In this post you will discover a 14-part crash course into applied machine learning using the Weka platform without a single mathematical equation or line […]

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A Gentle Introduction to XGBoost for Applied Machine Learning

Last Updated on April 22, 2020 XGBoost is an algorithm that has recently been dominating applied machine learning and Kaggle competitions for structured or tabular data. XGBoost is an implementation of gradient boosted decision trees designed for speed and performance. In this post you will discover XGBoost and get a gentle introduction to what is, where it came from and how you can learn more. After reading this post you will know: What XGBoost is and the goals of the […]

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