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The best machine learning platforms power email spam filters, ad recommendation engines, chatbots and even self-driving cars. Machine learning technology also powers security and network analytics, helping to root out and identify potential risks and intrusions. Enterprises even use the technology for the predictive maintenance of complex machinery, helping to identify potential malfunctions before they become expensive repairs.
In fact, machine learning platforms are so common as to belie machine learning's reputation as the highest of high tech. And to be sure, a close look reveals the tech to be highly advanced.
Machine learning most accurately describes algorithms that enable applications to make accurate outcome predictions without overt programming or user intervention. Essentially, machine learning models input and analyze data from disparate sources, apply statistical analysis, and predict an outcome. The learning comes from the fact that the algorithm refines outcomes as new data emerges. Machine learning algorithms are similar to predictive analytics and data mining in that they search for and identify data trends, adjusting actions as new patterns emerge.
Machine learning algorithms greatly vary in complexity, and they include decision trees, clustering and reinforcement learning, in both supervised and unsupervised fashion.
This is why it's important for an enterprise to understand the technology and the enterprise's needs before making a machine learning platforms comparison and buying decision. In this buyer's guide, machine learning experts walk potential buyers through the process, explaining the technology, the business considerations and the vendors and products that make up the market.
Enterprise data is vast and ever-growing, and it's full of potential insights. Organizations that can glean those insights and predict outcomes will have a competitive advantage. That's why considering the best machine learning platforms for the company's specific needs is vital.