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What is Machine Learning? | SAP

The simplest machine learning definition

Machine learning technology teaches computers how to perform tasks by learning from data – instead of being explicitly programmed.


Illustration of a human empowered with machine learning

Introduction to machine learning

Machine learning uses sophisticated algorithms to “learn” from massive volumes of Big Data. The more data the algorithms can access, the more they can learn. Real-world machine learning examples are everywhere. Think of personalized product recommendations on Amazon, facial recognition on Facebook, or fastest route suggestions in Google Maps. 


Illustration of the human brain

What is a neural network?

Neural networks – aka artificial neural networks – are a type of machine learning that is loosely based on how neurons work in the human brain. They are computer programs that use multiple layers of nodes (or “neurons”) operating in parallel to learn things, recognize patterns, and make decisions in a human-like way. 

Illustration representing a neural network in deep learning

What is deep learning?

Deep learning is a “deep” neural network that includes many layers of neurons and a huge volume of data. This advanced type of machine learning can solve complex, non-linear problems – and is responsible for AI breakthroughs such as natural language processing (NLP), personal digital assistants, and self-driving cars. 

Illustration of the human brain learning new information

Supervised vs. unsupervised learning

Supervised learning algorithms are trained using data that includes the correct answers. They build models that map the data to the answers – and then use these models for future processing. Unsupervised algorithms learn from data without being given the correct answers. They use large, diverse datasets to self-improve. 

Machine learning basics and best practices for business


5 machine learning lessons from fast learners

Explore the five key traits of machine learning leaders. These “fast learners” are using the technology to significantly improve performance across a range of business functions – from HR and finance to marketing and logistics.

Machine learning 101

Read up on the different types of machine learning techniques, use cases, and benefits for business. Determine if machine learning technology is right for your company, and get practical guidance on how to build a smart AI strategy.

The benefits of machine learning in business


Faster decisions

Machine learning algorithms can prioritize and automate decision making. They can also flag opportunities and smart actions that should be taken immediately – so you can achieve the best results.


Artificial intelligence doesn’t just look at historical data. It can process real-time inputs – so you can adjust on the fly. Think of cars that can automatically stop before rear-ending another vehicle.

Algorithmic business

An “algorithmic business” uses advanced machine learning algorithms to achieve a high level of automation. Making the shift can pave the way for innovative new business models, products, and services.

Deeper insights

Machine learning can analyze big, complex, and streaming data, and find insights – including predictive insights – that are beyond human capabilities. It can then trigger actions based on those insights.


With smart, machine learning-supported business processes, you can dramatically improve efficiency. Plan and forecast accurately, automate tasks, reduce costs, and even eliminate human error.

Better outcomes

From triggering smart actions based on new opportunities and risks, to accurately predicting the results of a decision before it is made – machine learning can help you drive better business outcomes.

Machine learning use cases in key sectors

Many different industries and lines of business are ripe for machine learning – particularly the ones that amass large volumes of data. Here are three sectors that are leading the way:


Illustration of a conveyer belt


Manufacturers collect a huge amount of data from plant sensors and the Internet of Things – which is perfect for machine learning. Computer vision and anomaly detection algorithms are used for quality control – and others are used
for everything from predictive maintenance and demand forecasting to powering new services. 

Illustration of a piggy bank


Few industries are better suited for machine learning than finance – given its high data volumes and historical records. Algorithms are used for trading stocks, approving loans, detecting fraud, assessing risks, and underwriting insurance. They’re even used for “robo advising” customers and aligning portfolios to user goals. 

Illustration of a healthy heart


Machine learning algorithms can process more data and spot more patterns than any team of researchers or doctors, no matter how many hours they put in. From medical image analysis and early cancer detection, to drug development and robot-assisted surgery – the machine learning possibilities in healthcare are endless. 

Machine learning research

SAP partners with top-tier universities to advance the use of machine learning for business.


Illustration of a magnifying glass

We’ve built a global partnership network with top universities such as MIT, Stanford, NYU, and the University of Amsterdam to explore the future of machine learning and advance the technology for business. Through this collaboration, we focus on a variety of machine learning research topics – and work on solving open AI challenges in a range of industries. This large pool of expertise helps us keep pace with the latest machine learning trends and deliver new techniques in the context of SAP solutions.

Machine learning training

Explore free, self-paced openSAP machine learning courses for everyone from beginners to developers.


Enterprise machine learning in a nutshell

Not sure how to use machine learning in a business context? This openSAP online machine learning course will guide you through the steps, from identifying use cases to prototyping.

Creating trustworthy and ethical AI

Join experts from the EU and SAP to learn about the societal and ethical implications of AI – and how to address them. This course is open to anyone with an interest in AI. 

Enterprise deep learning with TensorFlow

Get a hands-on intro to deep learning using Google TensorFlow. Created for data scientists and developers, this online course focuses on building models for enterprise problems.

Stay on top of machine learning trends


Markus Noga

VP of Machine Learning


Bringing transparency into AI

There is a growing demand to understand how AI and machine learning models and algorithms work, especially when there is an expanding number of machine learning cases without humans in the loop.

Maricel Cabahug

Chief Design Officer


Designing AI for people

The idea that a non-biological creation can learn, solve complex goals, and flourish in our world is a mighty leap forward. Where will it take us? How will we steer this emerging powerhouse that so many in the world are creating?

Robin Meyerhoff

Robin Meyerhoff

Brand Journalist


Three ways AI will transform customers’ experience

Retailers are exploring ways to improve the customer experience across all engagement points, including marketing, buying, and after-sales service. Discover the strategies and AI tools they’re using.

Explore SAP Leonardo Machine Learning

Build your intelligent enterprise with a machine learning platform and software that unite human expertise and computer insights.


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