Technology

Exploring the Horizon: Recent Advances in Deep Learning

 Deep Learning is defined as a subfield of machine learning that relies on artificial neural networks to learn from large amounts of data.

Artificial neural networks are inspired by the functioning of the human brain. They are composed of layers of interconnected units, called neurons, that process and transmit information. As the network receives data, it learns to identify patterns and perform specific tasks. Unlike other machine learning methods, deep learning does not require data to be predefined or structured. It can learn from raw data, such as images, text, and audio.

Within the wide range of applications, deep learning is mostly used in:

• Data science.
• Commerce (retail).
• Computer vision, speech recognition, natural language processing and bioinformatics.
• Personalized marketing based on people's preferences.
• Search for similar products based on images.
• Determining brand or company logos in images.
• Monitoring people's sentiment about a product at its launch through real-time image processing.

Deep learning has many advantages, including high accuracy in tasks that are difficult for other machine learning methods. We also find the ability of machine learning, in large amounts of data without the need for human intervention and, finally, the versatility of uses, Deep learning can be used in a wide range of applications, in various industry sectors.

On the other hand, the disadvantages are few, but could limit managers to invest in a deep learning system for their business, such as the difficulty of interpretation, it is difficult to understand how deep neural networks work when making decisions; it requires processing power which translates into costly investment at the computational level; finally, deep learning can be susceptible to bias in the data with which it is trained, so it requires extra attention to this step of the process.

As a powerful technology, deep learning is revolutionizing the way we interact with computers, allowing us to develop and design applications that are smarter, more accurate and adaptive than ever before.

If you want to read more about Deep learning, here is a list of additional resources

• https://developer.ibm.com/learningpaths/get-started-with-deep-learning/an-introduction-to-deep-learning/
• https://blogs.sas.com/content/subconsciousmusings/2020/04/06/getting-started-with-deep-learning-using-the-sas-language/
• https://www.iberdrola.com/innovation/digital-transformation

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09 de Abril, 2024