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Understanding of Machine Learning with Deep Learning: Architectures, Workflow, Applications and Future Directions

📅 Published: April 25, 2023 👤 Mohammad Mustafa Taye 📖 Computers 📊 955 citations
AI-Generated Summary

In recent years, deep learning (DL) has been the most popular computational approach in the field of machine learning (ML), achieving exceptional results on a variety of complex cognitive tasks, matching or even surpassing human performance. Lastly, we provide additional issues and recommended solutions to assist researchers in comprehending the existing research gaps.

⚡ This is an original paraphrased summary — not copied from the abstract. Full paper available at the source link below.

Key Findings
  • 1 Deep learning technology, which grew out of artificial neural networks (ANN), has become a big deal in computing because it can learn from data.
  • 2 The ability to learn enormous volumes of data is one of the benefits of deep learning.
  • 3 In the past few years, the field of deep learning has grown quickly, and it has been used successfully in a wide range of traditional fields.
Why It Matters

This research advances how AI systems learn, reason, and solve problems — with direct implications for automation and scientific discovery.

This summary is based on publicly available metadata and abstract. For the full research paper, visit the original source:

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