Deep Learning VS Machine Learning

The buzz surrounding artificial intelligence or AI has increased over the years and improvements are constantly being made to the way organisations function and operate with the integration of AI and similar technologies.

With AI, machines can have skills like learning, reasoning and problem solving, which are usually displayed by humans. Replicating human intelligence is one of the main goals of artificial intelligence and other goals include an intelligence connection of perception and action and solving knowledge-intensive tasks.

Advantages of artificial intelligence include high accuracy, fewer errors, high speed and reliability. AI also plays a key role in public utilities, whether in relation to transport, security, or communication.

When implementing AI-powered software and tools, we must remember that there are several subsets to artificial intelligence. These subsets include speed recognition, robotics, and natural language processing. Deep learning and machine learning are also subsets of artificial intelligence.

A simplified definition of AI is the ability for machines to mimic human intelligence. Machine learning enables machines to improve at tasks with experience. A subset of this is deep learning, where a machine trains itself to perform a task.

In order to fully understand the difference between deep learning and machine learning, however, it is necessary to take a closer look at the technologies.

Deep Learning

If your organisation works with AI service providers to develop certain products or enhance business operations, you may have come across the concept of deep learning. Deep learning is based on artificial neutral networks, the structure of which consists of multiple input, output and hidden layers.

When there is an input of data into a layer, units transform the data into information that will be used by the next layer for certain predictive tasks. This structure enables machines to train themselves to perform a task.

There are two key components required by deep data that delayed its use to some extent. The first component is labelled data, which deep learning requires large amounts of. The second is substantial and high-performing computing power.

However, today, we see the application of deep learning in various sectors and industries. One of the best examples of deep learning application is automated driving or self-driving cars. Deep learning is used in this instance to automatically detect objects like traffic lights as well as pedestrians.

In the industrial sector, deep learning is used to detect persons standing too close to heavy machinery, thus increasing worker safety.

These are just two examples of how AI service providers can enhance or improve working conditions or products with the use of deep learning.

Machine Learning

In machine learning, the machine or the learning model requires some guidance when improving its ability to carry out tasks. The key steps of machine learning start with data being fed into an algorithm. The data is then used to train a model, which needs to be tested and deployed.

The deployed model is then used to carry out an automated predictive task.

There are three key methods used by a machine learning consultancy and these are supervised machine learning, unsupervised machine learning, and semi-supervised machine learning.

One of the main differences between these methods is the type of data sets used, with supervised machine learning using labelled data sets and unsupervised machine learning using unlabelled data sets. Semi-supervised machine learning uses a smaller labelled data to guide classification and use a larger unlabelled data set for feature extraction.

Digital assistants are one of the best examples for machine learning as they are slowly becoming a regular household item. Digital assistants as well as other voice-driven applications like GPS use natural language processing or NLP.

You may also find the application of machine learning in digital marketing and customer service tools like chatbots. The recommendations you receive on various applications are also powered by machine learning.

To many, the difference between deep learning and machine learning may seem negligible but a development company that specializes in artificial intelligence can provide the best deep learning or machine learning strategies, tools and products to suit your requirements.