Over the past few weeks, we’ve been talking a lot about machine learning. Previously, we covered what machine learning is and how it solves Big Data challenges. In this post, we’re exploring human-guided machine learning — what it is and the benefits it offers.
There are three general types of machine learning: supervised, unsupervised, and reinforcement learning. Human-guided machine learning is a type of supervised learning, which uses a set of human-labeled training data to develop a model. In supervised learning, the algorithm learns a set of inputs along with corresponding correct outputs. The training data used to create a machine learning model is assumed to be ground truth, meaning that its validity is not questioned–however, the model must still be tested for accuracy before it can be deployed. There are also subsets of supervised learning known as active learning, or semi-supervised learning, where the machine learning model is improved with each additional correction or piece of information collected. This is where humans come in.
Human-guided machine learning is a process whereby subject matter experts accelerate the learning process by teaching the technology in real-time. For example, if the machine learning model comes across a piece of data it is uncertain about, a human can be asked to weigh in and give feedback. The model then learns from this input, and uses it to make a more accurate prediction the next time. Human-guided machine learning works from the bottom up by first using algorithms to conduct the heavy lifting of identifying relationships within the data, and engaging humans when necessary for training or validation. This means that, inevitably, the amount of time a human needs to spend performing a specific task will decrease as the machine learning accuracy increases.
This is important, mainly because of the sheer volume and variety of datasets that enterprises are tasked with managing today. Given the right solution, mastering large, diverse datasets through machine learning is significantly easier than creating and managing a network of custom rules and formulas. And, with human-guided machine learning, technical or data science knowledge isn’t even required. All that’s needed are subject matter experts who know the ins and outs of your data, and can tell the model whether, in fact, two similar names in your database are actually the same customer.
There are numerous benefits to human-guided machine learning, including the following:
To learn more about how Tamr uses human-guided machine learning to improve the data unification process, please reach out or schedule a demo. And to read more about machine learning and its benefits for Big Data challenges, download our ebook below.