Machine Learning is a multidisciplinary field and it can be very confusing when you are getting started to differentiate machine learning from the closely related fields of Artificial Intelligence and Data Mining. In this post you will learn about those fields that are related to machine learning. Specifically, you will learn about the boundaries of […]
What is Machine Learning? We can read authoritative definitions of machine learning, but really, machine learning is defined by the problem being solved. Therefore the best way to understand machine learning is to look at some example problems. In this post we will first look at some well known and understood examples of machine learning […]
Hello, my name is Jason Brownlee, PhD. I’m a father, husband, professional developer, and machine learning practitioner. I have a Masters and PhD degree in Artificial Intelligence and I’ve worked on machine learning systems for defense, startups, and severe weather forecasting. I started this community for two main reasons: 1) Because I find machine learning […]
Unit testing is a method for testing software that looks at the smallest testable pieces of code, called units, which are tested for correct operation. By doing unit testing, we can verify that each part of the code, including helper functions that may not be exposed to the user, works correctly and as intended. The […]
Python has become a de facto lingua franca for machine learning. It is not a difficult language to learn, but if you are not particularly familiar with the language, there are some tips that can help you learn faster or better. In this post, you will discover what the right way to learn a programming […]
Machine learning and deep learning models, like those in Keras, require all input and output variables to be numeric. This means that if your data contains categorical data, you must encode it to numbers before you can fit and evaluate a model. The two most popular techniques are an integer encoding and a one hot […]
Human activity recognition, or HAR, is a challenging time series classification task. It involves predicting the movement of a person based on sensor data and traditionally involves deep domain expertise and methods from signal processing to correctly engineer features from the raw data in order to fit a machine learning model. Recently, deep learning methods […]
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 […]
Exploring and applying machine learning algorithms to datasets that are too large to fit into memory is pretty common. This leads to questions like: How do I load my multiple gigabyte data file? Algorithms crash when I try to run my dataset; what should I do? Can you help me with out-of-memory errors? In this […]
Long Short-Term Memory (LSTM) networks are a type of recurrent neural network capable of learning order dependence in sequence prediction problems. This is a behavior required in complex problem domains like machine translation, speech recognition, and more. LSTMs are a complex area of deep learning. It can be hard to get your hands around what […]
