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Learn the difference between Artificial Intelligence(AI), Machine Learning(ML), and Deep Learning(DL). Read and compare Deep Learning vs Machine Learning vs Artificial Intelligence.<br><br>Read More: https://www.botreetechnologies.com/blog/artificial-intelligence-vs-machine-learning-vs-deep-learning-difference<br>
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Artificial Intelligence Vs. Machine Learning Vs. Deep Learning
You might be confused about whether you should implement Artificial Intelligence Systems, Machine Learning Programs, or Deep Learning Algorithms in your organization for digital transformation. Let us clear this confusion for you.
What is Artificial Intelligence(AI)? Artificial Intelligence is the technique of developing machines that imitate human behaviour. It provides objects, machines, and systems the ability to simulate real-world actions.
Think of this way - Artificial Intelligence(AI) systems are machines that think and act as humans do. They have an intelligent brain, just like humans do. It is useful to your organization in ways you can’t even imagine - an accurate visual perception of data, speech recognition, extracting insights from data, translation of documents and languages, and much more.
What is Machine Learning(ML)? Machine Learning is the building blocks behind Artificial Intelligence systems. You might have read somewhere about AI and ML and probably gotten confused.
You may also think that AI is a subset of Machine Learning (ML), but it’s the other way around. Machine Learning is a subset of Artificial Intelligence. Machine Learning is a technique, approach, or process for implementing Artificial Intelligence which involves parsing massive amounts of data, learning from that data, and making predictions based on that.
Types of Machine Learning SUPERVISED LEARNING UNSUPERVISED LEARNING REINFORCEMENT LEARNING
Supervised Learning When the Machine Learning algorithm comes across new data, it delivers the correct output based on these predefined parameters. As it receives more data, it corrects itself and makes accurate predictions. Unsupervised Learning When any input is given, it will go to the appropriate cluster of data and use it to deliver the output. Netflix saves the user’s watch history and delivers content that is based on history. A classic case of data clustering! Reinforcement Learning It involves making sequential decisions through Machine Learning algorithms for your business. The output depends on the current input, and the next input depends on the previous output.
What is Deep Learning(DL)? Deep Learning algorithms are much more complex than simple Machine Learning algorithms. They make use of natural language processing combined with neural network development.
Neural networks are based on the biological neural networks that we have in our brains. It involves interconnecting different neurons(inputs in the case of Deep Learning) to form an output. Deep Learning algorithms are highly advanced, and they involve much more computation complexity than Machine Learning programs. Here’s a good example by geeksforgeeks - Through a Machine Learning algorithm implemented in a flashlight(for the sake of understanding), the model will learn and train itself to switch on the flashlight whenever you say “dark”.
Now that you know what each of them is, you can clearly make the decision about which one to implement in your organization. If you need more help in understanding and choosing the right digital transformation technology, you can Talk for FREE with our ML experts, AI experts or DL experts.
