Machine Learning vs. Deep Learning [Explained]

AI has been a hot topic for several years now. Not just only in the world of new technologies but also in business. Many new concepts related to this technology have appeared in the public space, such as machine learning (ML) or deep learning (DL). Sometimes all these technologies are used interchangeably, which is unfortunately wrong. What are the main differences between the terms used to describe these two AI-based solutions artificial intelligence?

Artificial intelligence has become so essential that tech giants are willing to pay a lot of money to take over startups to develop them. For example, consider the British startup DeepMind, for which Google paid over 500 million USD and implemented the technology of facial and voice recognition developed by Google.

In the beginning, it should be clear that both these concepts, Machine Learning and Deep Learning, are part of the so-called Artificial Intelligence. AI deals with the creation of models of intelligent behavior and programs and systems to simulate these behaviors. In this way, problems that cannot be solved using standard, classical algorithms are solved.

Machine Learning

Machine learning enables programs and algorithms to learn from data and experience without human assistance. Hence the name–it’s all about machine(s) learning (themselves). Usually, the machine learning process takes place in 4 steps:

  • Entering the data source into the algorithm.
  • Use of this data to obtain a result.
  • Comparing the outcome with the control data.
  • Remembering the results and using them in subsequent iterations related to the processing of the entered data set.

Although the concept of machine learning may seem complicated and is mainly associated with technologies that we will deal with in the future, in practice, it is not. Machine learning already has several applications in the solutions we use every day.

Deep Learning

Deep learning is a more advanced version of ML. The deep learning algorithms are based on neural networks that have:

  • An input layer
  • Hidden layers
  • An output layer

This high complexity means that you can solve much more complex problems using more extensive data sources and big data. The human brain works likewise when it solves a problem. To find the answer, it passes queries to different areas of the brain. When the individual layers process information in the deep neural network, the system finds the appropriate identifiers. Thanks to them, it can correctly classify the processed data.

Although machine learning has become the dominant area of research in AI, these systems still have some limitations. Unlike machine learning, most deep learning is done unsupervised. Among other things, this involves the origination of large-scale neural networks that allow a computer to learn and think for itself without the need for direct human intervention.

Machine Learning and Deep Learning in Business: Usability

Artificial intelligence algorithms, with implemented machine learning and deep learning mechanisms, are now used everywhere–from simple chatbots on websites, through voice assistants such as Siri, road sign recognition systems supporting drivers, automatic translation systems, to autonomous vehicle software and management software flight and target tracking (like in F35 fighters).

In business, especially in marketing, AI plays an increasingly important role. We currently use machine learning and deep learning algorithms to personalize advertising content and to propose materials and products that a person may be interested in. This technology also allows you to track consumer behavior. ML and DL permit you to analyze large amounts of complex data as well as streaming data. Often this is information collected on an ongoing basis from social media. This data allows you to conclude necessary to develop an accurate business analysis. Thanks to this, you can make the right decisions and direct actions.

Machine learning algorithms can also prioritize or automate decision-making plus signal opportunities and indicate the right actions to take immediately. Therefore, for many years they have been a part of virtually all business analytics systems. They also work well as part of IT security systems. If you want to know how ML and DL can develop your business, contact Addepto specialists. The team of experts is open to new challenges and will be happy to prepare individual technological solutions based on machine learning and deep learning for you.

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