Articles About Machine Learning

Learning Vector Quantization for Machine Learning

Last Updated on August 15, 2020 A downside of K-Nearest Neighbors is that you need to hang on to your entire training dataset. The Learning Vector Quantization algorithm (or LVQ for short) is an artificial neural network algorithm that lets you choose how many training instances to hang onto and learns exactly what those instances should look like. In this post you will discover the Learning Vector Quantization algorithm. After reading this post you will know: The representation used by […]

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Support Vector Machines for Machine Learning

Last Updated on August 15, 2020 Support Vector Machines are perhaps one of the most popular and talked about machine learning algorithms. They were extremely popular around the time they were developed in the 1990s and continue to be the go-to method for a high-performing algorithm with little tuning. In this post you will discover the Support Vector Machine (SVM) machine learning algorithm. After reading this post you will know: How to disentangle the many names used to refer to […]

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Bagging and Random Forest Ensemble Algorithms for Machine Learning

Last Updated on August 15, 2020 Random Forest is one of the most popular and most powerful machine learning algorithms. It is a type of ensemble machine learning algorithm called Bootstrap Aggregation or bagging. In this post you will discover the Bagging ensemble algorithm and the Random Forest algorithm for predictive modeling. After reading this post you will know about: The bootstrap method for estimating statistical quantities from samples. The Bootstrap Aggregation algorithm for creating multiple different models from a […]

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Boosting and AdaBoost for Machine Learning

Last Updated on August 15, 2020 Boosting is an ensemble technique that attempts to create a strong classifier from a number of weak classifiers. In this post you will discover the AdaBoost Ensemble method for machine learning. After reading this post, you will know: What the boosting ensemble method is and generally how it works. How to learn to boost decision trees using the AdaBoost algorithm. How to make predictions using the learned AdaBoost model. How to best prepare your […]

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6 Questions To Understand Any Machine Learning Algorithm

Last Updated on August 12, 2019 There are a lot of machine learning algorithms and each algorithm is an island of research. You have to choose the level of detail that you study machine learning algorithms. There is a sweet spot if you are a developer interested in applied predictive modeling. This post describes that sweet spot and gives you a template that you can use to quickly understand any machine learning algorithm. Kick-start your project with my new book […]

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Machine Learning Algorithms Mini-Course

Last Updated on August 12, 2019 Machine learning algorithms are a very large part of machine learning. You have to understand how they work to make any progress in the field. In this post you will discover a 14-part machine learning algorithms mini course that you can follow to finally understand machine learning algorithms. We are going to cover a lot of ground in this course and you are going to have a great time. Kick-start your project with my […]

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Python Ecosystem for Machine Learning

Last Updated on August 21, 2019 The Python ecosystem is growing and may become the dominant platform for machine learning. The primarily rationale for adopting Python for machine learning is because it is a general purpose programming language that you can use both for research and development and in production. In this post you will discover the Python ecosystem for machine learning. Kick-start your project with my new book Machine Learning Mastery With Python, including step-by-step tutorials and the Python source code files for […]

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Introduction to the Python Deep Learning Library Theano

Last Updated on August 19, 2019 Theano is a Python library for fast numerical computation that can be run on the CPU or GPU. It is a key foundational library for Deep Learning in Python that you can use directly to create Deep Learning models or wrapper libraries that greatly simplify the process. In this post you will discover the Theano Python library. Kick-start your project with my new book Deep Learning With Python, including step-by-step tutorials and the Python […]

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Crash Course in Python for Machine Learning Developers

Last Updated on August 21, 2019 You do not need to be a Python developer to get started using the Python ecosystem for machine learning. As a developer who already knows how to program in one or more programming languages, you are able to pick up a new language like Python very quickly. You just need to know a few properties of the language to transfer what you already know to the new language. In this post, you will get a crash […]

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Introduction to the Python Deep Learning Library TensorFlow

Last Updated on December 20, 2019 TensorFlow is a Python library for fast numerical computing created and released by Google. It is a foundation library that can be used to create Deep Learning models directly or by using wrapper libraries that simplify the process built on top of TensorFlow. In this post you will discover the TensorFlow library for Deep Learning. Kick-start your project with my new book Deep Learning With Python, including step-by-step tutorials and the Python source code […]

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