Scalable Machine Learning on Spark. Offered by IBM. This course will empower you with the skills to scale data science and machine learning (ML) tasks on Big Data sets using Apache Spark.
Machine Learning is part of an encyclopedic known as Artificial Intelligence. It evolved from the study of pattern recognition and computational learning theory in artificial intelligence, machine learning explores the study and construction of algorithms that can learn from and make predictions on data — such algorithms overcome following strictly static program instructions by making data-driven predictions or decisions, through building a model from sample inputs.
We can broadly categorize machine learning into supervised and unsupervised categories based on the approach. There are other categories as well, but we’ll keep ourselves to these two:
- Supervised learning works with a set of data that contains both the inputs and the desired output — Supervised learning is further divided into two broad sub-categories called classification and regression:
- Classification algorithms are related to categorical output, like whether a property is occupied or not
- Regression algorithms are related to a continuous output range, like the value of a property
- Unsupervised learning, on the other hand, works with a set of data that only has input values.
Most popular Data Science and Machine Learning courses — August 2020. This list was last updated in August 2020 — and will be updated regularly so as to keep it relevant
Artificial Intelligence, Machine Learning, and Data Science are amongst a few terms that have become extremely popular amongst professionals in almost all the fields.
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In this article, I clarify the various roles of the data scientist, and how data science compares and overlaps with related fields such as machine learning, deep learning, AI, statistics, IoT, operations research, and applied mathematics.
In this tutorial on "Data Science vs Machine Learning vs Artificial Intelligence," we are going to cover the whole relationship between them and how they are different from each other.