Machine Learning Algorithms
What are Machine Learning Algorithms?
Algorithms are step-by-step computational procedures for solving a problem, similar to decision-making flowcharts, used for information processing, mathematical calculation, and other related operations.
Machine learning relies on algorithms to build models that reveal patterns in data, which in turn allow businesses to uncover insights and make predictions they can use to improve operations, better understand customers, and solve other business problems. There are many different algorithms, but most data scientists rely on a small set with which they are familiar.
Why are Machine Learning Algorithms important?
Algorithms are the heart of machine learning solutions. Data scientists use complex algorithms as building blocks for more efficient logical problem-solving. These algorithms take a lot of time and skill to produce, but without them, we wouldn’t have basic math, let alone be able to identify which families are likely best suited to become foster parents.
Machine Learning Algorithms + DataRobot
With traditional data science methods, running a single algorithm can be prohibitively difficult and time-consuming and includes complicated and technical data science processes like feature engineering. The DataRobot automated machine learning platform automates the model building process and runs dozens of models in parallel. This increases model diversity and cuts down the time it takes to build models, reducing time-to-value and resource requirements of machine learning projects.