Semi-supervised learning is a learning problem that involves a small number of labeled examples and a large number of unlabeled examples. Learning problems of this type are challenging as neither supervised nor unsupervised learning algorithms are able to make effective use of the mixtures of labeled and untellable data. As such, specialized semis-supervised learning algorithms […]
Optimization refers to finding the set of inputs to an objective function that results in the maximum or minimum output from the objective function. It is common to describe optimization problems in terms of local vs. global optimization. Similarly, it is also common to describe optimization algorithms or search algorithms in terms of local vs. […]
Optimization is a field of mathematics concerned with finding a good or best solution among many candidates. It is an important foundational topic required in machine learning as most machine learning algorithms are fit on historical data using an optimization algorithm. Additionally, broader problems, such as model selection and hyperparameter tuning, can also be framed […]
Data preparation is an important part of a predictive modeling project. Correct application of data preparation will transform raw data into a representation that allows learning algorithms to get the most out of the data and make skillful predictions. The problem is choosing a transform or sequence of transforms that results in a useful representation […]
Data preparation is the transformation of raw data into a form that is more appropriate for modeling. It is a challenging topic to discuss as the data differs in form, type, and structure from project to project. Nevertheless, there are common data preparation tasks across projects. It is a huge field of study and goes […]
Machine learning involves the use of machine learning algorithms and models. For beginners, this is very confusing as often “machine learning algorithm” is used interchangeably with “machine learning model.” Are they the same thing or something different? As a developer, your intuition with “algorithms” like sort algorithms and search algorithms will help to clear up […]
Classification is a predictive modeling problem that involves predicting a class label for a given example. It is generally assumed that the distribution of examples in the training dataset is even across all of the classes. In practice, this is rarely the case. Those classification predictive models where the distribution of examples across class labels […]
In this post, we will take a tour of the most popular machine learning algorithms. It is useful to tour the main algorithms in the field to get a feeling of what methods are available. There are so many algorithms that it can feel overwhelming when algorithm names are thrown around and you are expected to […]
Computer vision is a subfield of artificial intelligence concerned with understanding the content of digital images, such as photographs and videos. Deep learning has made impressive inroads on challenging computer vision tasks and makes the promise of further advances. Before diving into the application of deep learning techniques to computer vision, it may be helpful […]
Deep learning is not a magic bullet, but the techniques have shown to be highly effective in a large number of very challenging problem domains. This means that there is a ton of demand by businesses for effective deep learning practitioners. The problem is, how can the average business differentiate between good and bad practitioners? […]
