deep learning for

USAGE SUMMARY

The phrase "deep learning for" is correct and usable in written English.
It can be used when discussing applications, research, or projects related to deep learning in various fields such as technology, healthcare, or finance. Example: "Deep learning for image recognition has revolutionized the way we analyze visual data."

✓ Grammatically correct

News & Media

Science

Human-verified examples from authoritative sources

Exact Expressions

43 human-written examples

Deep learning, for example, which underlies technologies from Siri to Google Translate, uses several interconnected processing layers, modelled after the neuronal strata that compose the cortex.

The New Yorker

They point out that Google bought eight robotics companies in a two-month period in 2014, from Boston Dynamics, which makes the BigDog robot, to DeepMind, specialising in deep learning for artificial intelligence.

The Guardian - Tech

"We didn't need deep learning for everything".

TechCrunch

Efficient Deep Learning for Stereo Matching.

EURASIP Journal on Image and Video Processing

"We use deep learning for better understanding your digital footprint of your own voice," he notes.

TechCrunch

Abbeel's lab has pioneered deep learning for robotics, including learning locomotion and visuomotor skills.

TechCrunch

Human-verified similar examples from authoritative sources

Similar Expressions

17 human-written examples

It's true that you can learn something a heck of a lot faster than the typical deep learning system, for instance.

The Guardian - Tech

In January 2014, Google bought DeepMind, a London-based "deep learning" startup, for £400m.

The Guardian - Tech

WeLink: Deep learning platform for identifying threats on social media.

TechCrunch

We implement DLBH to learn deep learning hashing for mobile location recognition in two main steps.

EURASIP Journal on Image and Video Processing

Chopra et al. [87] propose a new Deep Learning model for domain adoption.

Journal of Big Data

Expert writing Tips

Best practice

When writing about "deep learning for", clearly specify the application or problem that deep learning is addressing to provide context and relevance to your audience.

Common error

Avoid using "deep learning for" without specifying the intended application. For instance, instead of saying "We use deep learning for our product", specify "We use deep learning for image recognition in our product" to provide clarity.

Linguistic Context

The phrase "deep learning for" functions as a prepositional phrase specifying the purpose or application of deep learning. Ludwig AI confirms its correct usage in diverse contexts.

Expression frequency: Very common

Frequent in

Science

33%

News & Media

65%

Formal & Business

2%

Less common in

Encyclopedias

0%

Wiki

0%

Reference

0%

Ludwig's WRAP-UP

In summary, "deep learning for" is a grammatically correct and widely used phrase that specifies the application or purpose of deep learning. Ludwig AI confirms its validity and common usage. It is frequently found in news media and scientific literature, emphasizing its role in solving various problems across technology and research. When using this phrase, ensure that the application is clearly defined to avoid vagueness. Alternatives include "deep learning in" and "applications of deep learning to", which offer slightly different nuances in meaning.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

using deep learning for

Focuses on the action of utilizing deep learning to achieve a particular goal.

deep learning in

Focuses on the field or area where deep learning is applied, rather than the explicit 'for' a specific purpose.

deep learning approaches for

Highlights methodologies in deep learning designed for specific applications.

deep learning methods for

Focuses on specific deep learning techniques employed for a particular task.

applications of deep learning to

Highlights the specific areas where deep learning techniques are implemented.

deep learning techniques for

Emphasizes the methods used within deep learning to achieve a specific outcome.

deep learning models for

Highlights the use of specific deep learning models in specific uses.

deep learning algorithms for

Emphasizes the computational procedures within deep learning that address particular problems.

deep learning's role in

Shifts focus to the function that deep learning plays within a broader process or field.

deep learning implementation for

Focuses on the practical aspects of putting deep learning into action.

FAQs

How can I use "deep learning for" in a sentence?

Use "deep learning for" to describe the application of deep learning techniques to a specific problem or task. For example, "Deep learning for image recognition has greatly improved accuracy in object detection".

What are some alternatives to "deep learning for"?

Alternatives include phrases like "deep learning in", "applications of deep learning to", or "using deep learning techniques for" depending on the nuance you want to convey. For example, consider "deep learning in healthcare".

Is it correct to say "deep learning for"?

Yes, "deep learning for" is a grammatically correct and commonly used phrase in technical and scientific writing to indicate the purpose or application of deep learning.

What's the difference between "deep learning for" and "deep learning in"?

"Deep learning for" emphasizes the specific goal or application, while "deep learning in" emphasizes the field or domain where deep learning is being used. For example, "deep learning for image segmentation" vs. "deep learning in medical imaging".