Machine Learning Algorithms
Machine learning (ML) is a subset of artifical intelligence (AI) that allows machines or systems to automatically learn to improve task performance. Machine learning programs can access data and learn from it without explict programming telling them to do so.
What are Machine Learning Algorithms?
Machine learning algorithms are an outgrowth of regular algorithms. When deployed in programs, ML algorithms automatically use the data provided to learn from experience. ML algorithms are divided into two phases -- a training phase and a testing phase -- and three common types:
- Supervised machine learning algorithm: These algorithms use labeled examples to apply past learnings to new data.
- Unsupervised machine learning algorithm: This type examines unlabeled datasets to find undiscovered patterns in the data.
- Semi-supervised machine learning algorithm: By combining both unlabeled and labeled data (usually more unlabeled), this type is deployed to improve learning accuracy.
Snowflake and Machine Learning
Snowflake's Data Cloud was designed from the ground up to integrate and support machine learning and AI-driven data science applications. Unlimited data storage and compute resources scale elastically to meet any need or demand. Combined with tight integrations to Spark, R, Qubole, and Python, Snowflake is an essential part of the Data Science Tech Stack.