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Deep Learning has been hailed by businesses across the globe as the next big technology in the realm of data science and artificial intelligence, and rightly so.

Widely used to facilitate automated hearing, image recognition, speech translation and recognition, Deep Learning is the same technology that powers driverless cars, teaching them to recognise signs like ‘stop’ and ‘go’, or to distinguish between a pedestrian and a lamppost.

It also powers voice-controlled functions in electronic devices like smartphones, tablets, or smart televisions.

In an increasingly technology-driven ecosystem, Deep Learning systems can have massive implications for any business, enabling them to take advantage of the massive volume of data they possess to enhance their overall operational efficiency, as well as develop new monetisation models.

What is Deep Learning?

Deep Learning is a machine learning technique which instructs computer show to learn by example, almost exactly like humans do.

Benefits of deep learning:

• Through Deep Learning models, a computer is taught how to collect and classify information directly from images, text, or sound; these models themselves are guided by neural network architectures and large data sets, which enable algorithms to learn new information through multi-layered processing
• Although Deep Learning is a specialised subset of Machine Learning, unlike the latter, it can automatically extract relevant information from raw data and perform classifications without any manual intervention
• Since Deep Learning models run on neural network architectures, they are also usually referred to as deep neural networks
• The word ‘deep’ separates them from conventional neural networks, which have two to three hidden layers at most. On the other hand, deep neural networks can have as many as 150 layers
• Deep Learning methods based on neural networks can also perform natural language tasks such as language modelling and processing, part-of-speech tagging, named entity recognition, sentiment analysis, and paraphrase detection, much more efficiently
• Thus, a key advantage of a deep network is that it can perform tasks with only a single end-to-end model, and without traditional, task-specific feature engineering.

Deep Learning for online learning platforms:

For online education or skilling platforms which own massive databases of visual content, categorising and managing them efficiently is difficult, thereby making all the data unusable.

However, machine learning techniques like Deep Learning help solve this problem, allowing these platforms to organise and classify their database of images.

Thus, by eliminating the need to spend numerous hours on sorting and tagging data manually, deep learning models allow online educational platforms to monetise their visual content and develop comprehensive learning modules.

Considering its wide potential use cases, knowledge of Deep Learning is currently one of the most sought-after skills for digital businesses.

More importantly, though, the demand for this technology presents a massive opportunity for young graduates and professionals to upskill and enhance their career prospects through industry-backed data science courses.

Source: https://www.indiatoday.in/education-today/featurephilia/story/what-is-deep-learning-this-is-how-online-education-websites-can-make-you-learn-deeply-1157476-2018-01-30