Examples of using Machine learning can in English and their translations into German
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Using machine learning can be simple.
Here is exactly where artificial intelligence and machine learning can help.
Machine learning can seem intimidating at first.
A combination of chatbots and machine learning can significantly increase the added value.
Machine learning can make extremely time-consuming methods a lot faster.
There are two main ways machine learning can improve quality assurance QA.
NTT Data now shows howsimulation data has to be prepared so that machine learning can come into play.
Even today, machine learning can predict and solve 86% of issues before they become a problem.
This exhibit shows how data mining, personal genomics and machine learning can be integrated into our daily lives.
Programmes using machine learning can employ algorithms to predict people's actions in order to, for example.
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.
In this context, machine learning can support decision-making through attack assessment and can already suggest response options.
Competitive edge through AI How artificial intelligence and machine learning can make production more efficient and secure global competitiveness.
AI and machine learning can drive business outcomes from cost savings and risk reduction to new products and better service.
The idea behind this is that Machine Learning can be used to automate numerous functions and workflows and thus make them more efficient.
Machine Learning can identify objects in one specific image or recognize actions based on changes in the object's state over time.
PowerMax, with its built-in machine learning, can help you maximize performance across all aspects of your EHR environment.
Machine learning can take all these into account to deliver personalized diagnosis and treatment, while optimizing healthcare resources.
Drebin clearly demonstrated that machine learning can be used to automatically classify Android apps based on certain aspects of their behavior.
Machine learning can provide companies with a competitive edge by solving problems and uncovering insights faster and more easily than conventional analytics.
Applying machine learning to IoT Machine learning can be used to achieve higher levels of efficiency, particularly when applied to the Internet of Things.
Machine learning can help analyze geographical data to uncover patterns that can more accurately predict the likelihood that a particular site would be the right location for generating wind or solar power.
By sifting and categorizing many examples, machine learning can objectively learn to recognize and identify specific external variables that, for example, give a voice its character.
Machine learning can discover elaborate and non-linear dependencies in the data and use them to generate models that can improve the relevance of search results beyond what can be conceived by human inspection.
Research shows how machine learning can help doctors discern between two very serious heart conditions with very similar symptoms.
See how modelling and machine learning can be used to understand complex patterns and relationships in your data.
Another plus: Machine learning can increase the volume and variety of big data, unearthing new sources that are larger and cheaper than the initial structured set.
A combination of chatbots and machine learning can significantly increase the added value, as the chatbot continuously learns from the dialogs and thus provides a better service.
Using AI-based machine learning could create USD 215 billion in added value for the automotive industry by 2025.
There are many areas- like reputation, cyber, supply chain and economic and climate risk scenarios-where machine learning could help companies better understand their risks," says Bruch.