Deep Learning vs Machine Learning vs AI

Today we look more in detail about these buzzwords which were estimated to replace 20% to 30% of the workforce in the next few years – Deep learning, Machine learning (ML) and Artificial intelligence (AI). What are the differences, their advantages, and disadvantages, use cases etc.  

Nowadays you often hear buzz words such as artificial intelligence, machine learning and deep learning all related to the assumption that one day machines will think and act like humans. Many people think these words are interchangeable but that does not hold true. One of the popular google search requests goes as follows “are artificial intelligence and machine learning the same thing?”

What is Deep Learning

Deep learning is a subset of machine learning which makes use of neural networks to analyse various factors. Deep learning algorithms use complex multi-layered neural networks where the abstraction level gradually increases by non-linear transformations of data input. To train such neural networks a vast number of parameters have to be considered to ensure the end solution is accurate. Some examples of Deep learning systems are speech recognition systems such as Google Assistant and Amazon Alexa. 

What is Machine Learning (ML)

ML is a subset of artificial intelligence (AI) that focuses on making computers learn without the need to be programmed for certain tasks. To educate machines three components are required – datasets, features, and algorithms.

• Datasets are used to train machines on a special collection of samples. The samples include numbers, images, text, or any other form of data. Creating a good dataset is critical and takes a lot of time and effort. 
• Features are important pieces of data that work as the key to the solution of the specific task. They determine when machines need to pay attention and on what. During the learning process the program learns to get the right solution during supervised learning. In the case of an unsupervised learning machine it will learn to notice patterns by itself.
• Algorithm is a mathematical model mapping method to learn the patterns in datasets. It could be as simple as a decision tree, linear regression. 

Artificial Intelligence (AI)

AI is like a discipline such as Maths or Biology. It is the study of ways to build intelligent programs and machines which can solve problems , think like humans, and make decisions on their own. Artificial intelligence is expected to be a $3 billion industry by year 2024. When artificial intelligence and human capabilities are combined, they provide reasoning capability which is always thought as human prerogative.  The AI term was coined in 1956 at a computer science conference in Dartmouth. AI was described as an attempt to model how the human brain works and based on this know-how creating more advanced computers. 

Comparison: Deep Learning vs Machine Learning vs AI

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