So, until now, you must be aware of the term machine learning, its types, applications, and working. We have ample information about machine learning. Let’s move to Deep learning and understand it. Deep learning is the most popular domain of Artificial Intelligence.
What is Deep Learning?
When we talk about Deep learning, it automatically strikes our mind. Is deep learning is similar to machine learning? If it’s similar what’s the difference which makes deep learning important.
Deep Learning is another domain of artificial intelligence that works exactly like the human brain in order to process data and create patterns. Deep Learning is part of the extended family of machine learning and also known as deep structured learning. This has been introduced to bring machine learning closer to its goal which is Artificial Intelligence.
The functioning of Deep learning is quite similar to machine learning. However, there is a slight difference that makes deep learning different from machine learning. Machine learning algorithms require structured data whereas deep learning networks functions on layers of ANN (artificial neural networks).
Let’s example this by a simple example: We all have heard about the new innovation in automobiles and must be aware of driverless cars. The fundamental technology behind such cars is deep learning which enables the various functioning of it without human assistance.
What’s the importance of Deep Learning?
Deep Learning has the most precise accuracy rate. Its ability to process various features makes deep learning an extremely powerful algorithm. This helps consumers to meet their expectations which is important for safety-critical applications.
The deep learning algorithm is important for knowledge application and knowledge-based predictions. Put it in another way, deep learning can be an extremely robust engine for producing desired results.
How does Deep Learning work?
To understand the working of deep learning in a better way. One must have brief knowledge about the terms of Artificial Intelligence and Machine learning. Artificial Intelligence is the duplication of human intelligence in computers. Whereas Machine Learning is the ability of a machine to learn using large data sets rather than hardcoded rules.
Deep learning is a subset of machine learning which allows computers to guide an AI’s output predictions. Even so, supervised and unsupervised learning is capable to train the AI.
Deep Learning vs Machine Learning
The easiest way to understand the fundamental difference between deep learning and machine learning is that deep learning is machine learning.
Comparison between machine learning and deep learning
- Machine learning algorithm mainly works on the low-end machines whereas deep learning algorithm is highly dependent on high-end machines.
- In machine learning, most of the features are identified by an expert and then hand-coded. On the contrary, deep learning tries to learn high-level data features.
- Deep learning algorithms take a long time to execute which is much more than the machine learning algorithm normal time taken. Deep learning requires much less time to test whereas machine learning takes longer than usual.
- Problem-solving approach of a machine learning algorithm is quite different as it is normally broken down the problem into different parts, solve them separately. Deep learning solves end to end problem.
Applications
- Self – driving cars
- Fraud news detection
- Language translation
- Pixel restoration
- Virtual assistant
- Visual recognition
- Healthcare
Deep Learning with MATLAB
MATLAB makes deep learning easy to use. Just with the use of a few codes MATLAB and you don’t need help from an expert. MATLAB allows you to build deep learning models with the use of minimal coding.
MATLAB can be used to learn and gain knowledge in the area of Deep Learning. MATLAB has a deep ability to unite various domains in a single workflow. It offers tools and different functions for deep learning algorithms such as computer vision and data analytic etc. This alternative approach can lead the better consequences in less time.
Solution using Deep Learning
Deep learning uses neural networks to solve the problem. The input data is sent via different levels of neural networks. This is very much similar to the human brain functioning and how it solves the problem.
Once the data is processed through different levels of the neural network, the system identifies the images. This algorithm didn’t require any structured data by each layer.
Future Trends in Deep Learning
The unprecedented growth in technologies, businesses are now looking for various alternatives that are best suited for their growth. The development in the field of machine learning and deep learning has become the need of the hour and companies are striving to inculcate deep learning in their business.