Fundamentals of Deep Learning
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Deep learning is a machine learning technique that teaches computers to essentially learn by example.
For instance, deep learning is a key technology behind driverless cars, enabling them to recognize a stop sign, or to distinguish a pedestrian from a lamppost.
Deep learning is also the technology behind voice control in consumer devices like phones, tablets, TVs, and hands-free speakers.
In aerospace and defense, deep learning is also utilized to identify objects using satellites that locate areas of interest and identify unsafe or safe zones for troops.
Then there’s industrial automation where deep learning helps to improve the safety of workers around heavy machinery by automatically detecting when objects or people are within an unsafe distance from a machine.
The electronics sector uses deep learning in speech translation and automated hearing. For instance, home assistance devices that respond to one’s voice and know one’s preferences are powered through deep learning applications.
Other applications include numerous everyday encounters and activities, such as virtual assistants, fraud detection, language translation, chatbots and service bots, colorization of black-and-white images, facial recognition and disease diagnoses.
In deep learning, a computer model learns to perform classification tasks directly from images, text, or sound. Deep learning models can achieve state-of-the-art accuracy, sometimes exceeding human-level performance.
Models are trained by using a large set of labeled data and neural network architectures that contain many layers.
Experts in this field believe with time and additional research opportunities, unsupervised deep learning methods may deliver models that will closely mimic human behavior
Unsupervised learning is a promising new technique in deep learning, in which instead of training a system with labeled data, it is trained to self-label the data using raw forms of data. Instead of using labeled data to train a system, the system will learn to label raw data.
Unsupervised learning, also known as unsupervised machine learning, uses machine learning algorithms to analyze and cluster unlabeled datasets. These algorithms discover hidden patterns or data groupings without the need for human intervention. Its ability to discover similarities and differences in information make it the ideal solution for exploratory data analysis, cross-selling strategies, customer segmentation, and image recognition.
Fundamentals of Deep Learning Course by Tonex
Fundamentals of Deep Learning is a 2-day training course address fundamentals of deep learning. This two-course online training program brings a hands-on approach to understanding the deep learning methods, algorithms, and computational tools used in modern engineering problem-solving.
Leveraging the rich experience of the faculty at
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Fundamentals of Deep Learning