What is Machine Learning?
Machine learning definition
Machine learning refers to the process by which computers develop pattern recognition, or the ability to continuously learn from and make predictions based on data, then make adjustments without being specifically programmed to do so. A form of artificial intelligence, machine learning effectively automates the process of analytical model building and allows machines to adapt to new scenarios independently.
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Why machine learning?
Whether or not you’re excited by the idea of artificial neural networks one day growing sophisticated enough to replicate human consciousness, there are undeniable practical advantages to machine learning, namely:
- Intelligent big data management – The sheer volume and variety of data being generated as humans and other environmental forces interact with technology would be impossible to process and draw insights from without the speed and sophistication of machine learning.
- Smart devices – From wearable devices that track health and fitness goals to self-driving cars to "smart cities" with infrastructure that can automatically reduce wasted time and energy, the Internet of Things (IoT) holds great promise, and machine learning can help make sense of this significant increase in data.
- Rich consumer experiences – Machine learning enables search engines, web apps, and other technology to customize results and recommendations to match user preferences, creating delightfully personalized experiences for consumers.
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HPE machine learning solutions
Server solutions from Hewlett Packard Enterprise are built to help customers realize real-time performance for their AI workloads. The HPE Apollo 6000 system is a deep learning platform designed to deliver unprecedented performance and scale in a relatively small footprint.
Deep learning is a subset of machine learning and has recently demonstrated significantly superior performance to some traditional machine learning approaches. Deep learning utilizes a combination of multi-layer artificial neural networks, data- and compute-intensive training, inspired by our latest understanding of human brain behavior. This approach has become so effective it’s even begun to surpass human abilities in many areas, such as image and speech recognition and natural language processing.
Cynkowanie przy wykorzystaniu sztucznej inteligencji i głębokiego uczenia
Dowiedz się, jak producenci łączą komputerowe wspomaganie prac inżynierskich (CAE), sztuczną inteligencję funkcjonującą w oparciu o dane oraz technologie głębokiego uczenia, aby usprawnić swoje działania, obsługiwać większą liczbę produktów i zwiększać zyski.
- Podnoszenie wartości produkcji dzięki sztucznej inteligencji i uczeniu maszynowemu
- Korzyści wynikające z głębokiego uczenia z wykorzystaniem komputerów wysokiej wydajności
- Wyjątkowe rozwiązania i zasoby w zakresie sztucznej inteligencji i głębokiego uczenia