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Data science has been termed as “sexiest job of the 21st century” by Harvard. And with all the recent hype around these terms like machine learning, artificial intelligence (AI), deep learning & data science, it is becoming confusing to separate them each other understand their true meaning.
They are also referred as electricity of this century therefore these industries offer some of the best opportunities for all kind of professionals.
Artificial intelligence, machine learning & deep learning are one of the hottest topics on planet earth today and people from all streams are trying to get into these promising fields.
As a result, if you look at the google trend for some these terms like “what is machine learning”, “what is artificial intelligence (AI)” or “what is deep learning”, you will find a constant increase in interest around these terms.
what is machine learning
what is artificial intelligence
what is deep learning
A lot of companies selling products or services based on machine learning or artificial intelligence or deep learning, tend to use these terms interchangeably which further contributes to confusion. A lot of people believe that machine learning, deep learning & artificial intelligence are same.
And this is far from truth.
Infact if you were to find out google trends for terms like;
1. Machine learning vs Artificial intelligence or
2. Machine learning vs deep learning or
3. Deep learning vs artificial intelligence
You will be shocked to see how many people are trying to understand the difference between these terms. You can also try variations like AI vs ML or ML or DL etc.
Have you been wondering about
OR
You will find this post useful.
In this post, I am going to cover the broad definition of machine learning, deep learning & artificial intelligence (AI).
So, before we move ahead with the differences between machine learning, artificial intelligence and deep learning, we need to understand these concepts at a high level.
What is artificial intelligence (AI)
What is machine learning
What is deep learning
You can think of “Science” subject from your school, it consisted- physics, chemistry and biology.
Similarly, artificial intelligence is the science in this case.
Artificial intelligence consists of machine learning.
Machine learning consist of various models including deep learning.
Deep learning is a special technology.
So, the question of machine learning vs artificial intelligence (ai vs ml) doesn’t arise because artificial intelligence encompasses machine learning.
Similarly, you can say that machine learning encompasses deep learning but there are few differences between most popular machine learning algorithms like logistic regression and deep learning.
To elaborate on some of these differences between most popular machine learning algorithms and deep learning, I have added this table. But remember, deep learning is subset of machine learning.
Machine Learning | Deep Learning |
|---|---|
Need Lesser Data than Deep Learning. | Need More Data. |
Can work comfortably with CPU | Can work with CPU but performance issues, need GPU for optimum performance. |
Need to manually define the features with supervised machine learning models. | Doesn’t need manual definition of features, model can automatically figure that out. |
Good and recommended when you need to control the feature definition and recreation. | Recommended when your focus is on output and not on ability to define feature but is not recommended if feature definition is important. |
Popular applications include classification models like fraud detection, email spam or not spam. | Popular applications include image classification, text classification. |
Some of the common examples of machine learning algorithm are – linear regression, logistic regression, KNN, k-means, random forest etc.
Some of the common examples of deep learning algorithm are- Convolutional neural network (CNN), recurrent neural network (RNN), long short-term memory (LSTM), generative adversarial network (GAN) etc.
If you still have any confusion, please leave your comment.
And yes, don’t forget to share.
About akhilendra
Hi Akhilendra,
It was quite an interesting read, can you please help me answer a question:
I am a fresher and want to start my career as an artificial intelligence engineer, could you please recommend some ways using which I can become a successful AI engineer.
Hi Rev, AI is like any other development activity as far as engineers are concerned. Probably, a bit more complicated than web development because you need to have basic understanding of statistics and better business acumen. In other tech fields, you could still manage if you don’t understand business or user problem but AI/ML is all about solving real life problems. I will suggest you to start with basics like applied statistics, how to use data visualization to convey information.
From there take it to next level and start using all the major ML models to understand how they help solving real problems. Then you can start learning deep learning like image recognition, sentiment analysis etc. But keep practicing, it’s all about practicing.
Thank you so much for your advice.
Cheers