{"id":2218,"date":"2026-08-10T08:54:43","date_gmt":"2026-08-10T08:54:43","guid":{"rendered":"https:\/\/nokobox.com\/index.php\/item\/udemy-deep-learning-zero-to-hero-hands-on-with-python-2024-1\/"},"modified":"2026-08-10T08:54:43","modified_gmt":"2026-08-10T08:54:43","slug":"udemy-deep-learning-zero-to-hero-hands-on-with-python-2024-1","status":"publish","type":"digital_item","link":"https:\/\/nokobox.com\/index.php\/item\/udemy-deep-learning-zero-to-hero-hands-on-with-python-2024-1\/","title":{"rendered":"Udemy \u2013 Deep Learning ZERO To HERO \u2013 Hands-On With Python 2024-1"},"content":{"rendered":"
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Description<\/span><\/h2>\n

Deep Learning Course ZERO To HERO \u2013 Hands-On With Python. ZERO To HERO Deep Learning Course \u2013 Hands-On With Python. Deep learning is a new part of machine learning that was introduced with the aim of bringing machine learning closer to artificial intelligence. Machine learning is a scientific discipline that examines the construction and study of algorithms that can learn from data. Such algorithms work by building a model from sample inputs and using it to make predictions or decisions, rather than strictly following program instructions. Machine learning is closely related to and often overlaps with computational statistics. A field that also specializes in forecasting. Through this training, we intend to learn and apply the concepts of deep learning with live projects. The course includes the following;<\/span><\/p>\n

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\u2022 Prediction on structured\/tabular data<\/span><\/p>\n

\u2022Advice<\/span><\/p>\n

\u2022 Image classification<\/span><\/p>\n

\u2022 Image segmentation<\/span><\/p>\n

\u2022 Object detection<\/span><\/p>\n

\u2022 Light transmission<\/span><\/p>\n

\u2022 Super resolution<\/span><\/p>\n

\u2022Sentiment analysis<\/span><\/p>\n

\u2022 Text generation<\/span><\/p>\n

\u2022 Time series (sequence) forecast<\/span><\/p>\n

\u2022 Machine translation<\/span><\/p>\n

Speech recognition<\/span><\/p>\n

\u2022 Answer the question<\/span><\/p>\n

\u2022 Similarity of the text<\/span><\/p>\n

\u2022 Image subtitles<\/span><\/p>\n

\u2022 Image of the generation<\/span><\/p>\n

\u2022 Image to image translation<\/span><\/p>\n

We will learn the following:<\/span><\/p>\n