Deep Learning |diːp ˈlɜːnɪŋ| — ⠴⣠⠎⣀⢘⡃⠔ ⢢⠨⡨⠃⢑⢒⠋⣀

Deep Learning is a subset of machine learning that involves the use of artificial neural networks to learn and make predictions or decisions based on large datasets. It is called "deep" because it involves multiple layers of interconnected nodes or neurons that can learn and extract features from data at different levels of abstraction. Deep learning has been successfully applied to various fields such as computer vision, natural language processing, and speech recognition, among others.

— ⠔⡌⢂⡨⠲⠲⠤ ⠌⣀⠓⢤⢒⠇⠌⠡ ⢢ ⠊⠩ ⡄⢰⠲⢐⢄⡁⠬⢄⠦⢑ ⡊⢊⠅⡂⢰⢃⢰⠣⢆ ⠑⣠⠔⣁⢤⣁⢂⣄⠱ ⠨⠦ ⠩⢒⢡⠉⠤⠤⡡ ⠢ ⢤⠰⣄⣠ ⠣⣈⡁⠎⡄⡅⢐⣐⠢⢅⠑⠌ ⡒⠩⣀⠒⠅⣄⡃ ⠬⢊⢰⠆⠙⠴⡤⠴⠜ ⠍⠪⢰⢌⣄ ⡃⡁⠨ ⠨⣄⡉⢈⡨⡘⢑⢘ ⡑⡌ ⣄⡔⠌⠃⡒⢘⢰⠨⢃ ⣂⢡⢐⠕⡐⢈ ⢉⠱ ⡤⢒⡁⢡⠃⠤ ⠦⢅⠋⡌⠑⡘⢈ ⡢⡌⠚⢅⠘⠸⠘ ⠬⡤⢘⠣⠌⡑ ⣀⢅⣁⡅ ⢈⡑⠚⣄⣠⢨⠔⣂⡔ ⢰⡃⡈⡆⠇⢰⡤⡠⠰⢑⢊ ⢄⢌⣠⡉⢄⠊⢁⠑ ⢐⡒⡔ ⠌⢆⠔⠅⢅⠃⡅ ⡁ ⠤⠪⡠⠎ ⡅⡃⢅⢐⢐⣁ ⡆⠔⡄⠙⡃ ⢑⠰⡊⠴⡠⠕⡈⢨⠥⣠⠦⠦⡠⠦⠑⠙ ⠘⡃⡒⠦⡌⡤ ⡠⣁⠅ ⡒⠅⡅⢘⢨⠨⠨⠴⢉ ⡤⢉⡒ ⣁⡁⠡⠕⡒⡉ ⡌⡊⡘⠌⡨⡨⡂ ⡘⢔ ⢨⠕⢁⢰⠊⢂⠬⠕⡑⠤ ⠆⡂⠖⡰⠥⠑ ⠤ ⡑⡂⠆⢆⢊ ⡒⢡ ⣄⡂⠑⠰⠕⡐ ⠅⢐⡌⢂⡢⠨ ⠅⡡⠆⡒⢒⠌⢘⢁⢄⣀⣀ ⠚⠜⠬⣁⡡⢊⡅ ⡃⢃⢉⠡⠕⡁⠍⠖ ⣄⠥⠨⡒⠔⠰⠋ ⠢⢐⡂⡂⠨⠜⠥⣄⡠⠎⠕⢃⢐⠔ ⠆ ⠎⠤⢂⡌⢂⡒ ⢈⠔⠴⡠⠉⡢⠓⠤ ⠋⡨⢄⡑⠕ ⣂⢈ ⢠⢢⡠⠴⡰⡑⢉⠬⡈⢌⢢⢒ ⠑⣠⡃⡈ ⢄⡘⢅⠱⡂⣂⠓ ⠇⢈⡅⠒⠖⣠⠪⡡⢆⠕ ⣂⢌⠢⠌ ⠑⠡ ⢃⢢⠅⡅⠜⠦⡌⡒⢅⢉⢤⢅⣠ ⢒⠤⣀⡆⡨ ⢤⠃⡂⠕⡁ ⣐⢉⠡⢂⠕⡒

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