One of the biggest challenges facing the medical industry is drug-resistant bacteria. Currently, there are some estimated 700,000 deaths due...
K-Nearest Neighbors is a machine learning technique and algorithm that can be used for both regression and classification tasks. K-Nearest Neighbors examines the labels of a...
Linear regression is an algorithm used to predict, or visualize, a relationship between two different features/variables. In linear regression tasks, there are two kinds of variables...
Support vector machines are a type of machine learning classifier, arguably one of the most popular kinds of classifiers. Support vector machines are especially useful for...
When you train a neural network, you have to avoid overfitting. Overfitting is an issue within machine learning and statistics where a model learns the patterns...
If you’ve read about how neural networks are trained, you’ve almost certainly come across the term “gradient descent” before. Gradient descent is the primary method of...
Deep learning systems are able to learn extremely complex patterns, and they accomplish this by adjusting their weights. How are the weights of a deep neural...
One of the fastest-growing areas of research in machine learning is the area of meta-learning. Meta-learning, in the machine learning context, is the use of machine...
Perhaps you’ve wondered how Facebook or Instagram is able to automatically recognize faces in an image, or how Google lets you search the web for similar...
“Big Data” is one of the commonly used buzz words of our current era, but what does it really mean? Here’s a quick, simple definition of...
One of the most powerful analytical tools in machine learning and data science in the confusion matrix. The confusion matrix is capable of giving the researchers...
Computer vision algorithms are one of the most transformative and powerful AI systems in the world, at the moment. Computer vision systems see use in autonomous...
Many of the biggest advances in AI are driven by artificial neural networks. Artificial Neural Networks (ANNs) are the connection of mathematical functions joined together in...
In machine learning, most tasks can be easily categorized into one of two different classes: supervised learning problems or unsupervised learning problems. In supervised learning, data...
Unstructured data is data that isn’t organized in a pre-defined fashion or lacks a specific data model. Meanwhile, structured data is data that has clear, definable...
