Deep learning, Artificial Intelligence, and Machine Learning are some of the fields that are in trend now, and since the talks about LaMBDA have surfaced, It has made quite an impression on users as well as the researchers. So, our motive is not to know or dig deeper into LaMBDA Bot, but simply with the help of such an advanced bot understand the technology that lies behind it and supports the whole system. So, now let's start.
Deep Learning VS Machine Learning VS Artificial Intelligence
Starting off our decision let us make things clear for ourselves, by differentiating between these three terms. And point to note here is unlike any other tutorial we will not be using these terms synonymously.
Artificial Intelligence (AI) – It is known as the ability of a machine. Note here is Machine. To copy a human behavior using some sort of logical rules, or decision trees, and even including deep learning or machine learning.
Machine Learning (ML) – It is the smaller picture of the broader element of Artificial intelligence, It is the Application of Artificial Intelligence that automatically learns from past experiences.
Deep Learning (DL) – While ML was a child of AI, DL is a child of ML. And these are the applications of Machine Learning that uses complex algorithms to train a model that is formed using multi-layers. Common tasks under this category are Speech, Image Recognition, and classification.
What is Deep Learning?
Deep learning as the name suggests, is in-depth knowledge. It comes under Machine Learning. Deep learning is related to the neural network (which is motivated by the structure and function of the brain). The main aim behind deep learning models is to create a human-like brain, that can learn and teach itself.
It is a form of AI, where the system/model is trained with an example instead of programming. Just like human understands. So, the deep learning models are created with multiple layers where some are hidden layers, If you were to ask a machine where a bottle placed in front of the machine is a bottle or not? The model would pass the data through multiple hidden layers and output if it is a bottle or not.
Some of the best AI that is working on Deep Learning –
Self Driving Cars – Tesla is the first thing that comes to my mind whenever the term “Self driving cars tossed”. And not only me, but you would also think of Tesla as the first option. Now, what Tesla cars have done is created a robust AI, that has managed to drive, and perform human operations without human intervention. And, These SDC (Self-driving cars) models are based on CNN.
Face Detection – In between thousand of people, now you can correctly find/identify the person based on their facial properties, classify them as male or female, age group, as well as classify them into different age groups. Nowadays, the face detection system can be seen everywhere like surveillance, Attendance system, infiltration monitoring, etc.
Trading and Finance – May Financial institutions, and individual traders rely on previous data to predict the next course of the market. But due to the manual activity, they can either process a little or past 2-3 years of data only. So, deep learning models help in providing more reliability to the system. Moreover, it is being used as a risk management tool to help people overcome situations like the Terra-Luna crypto crash.
Data Mining – It is related to computer programs finding hidden patterns, Deep learning is being used to find more hidden insights in large datasets which can be related to anything including predicting the next question in a chatbot to credit card fraud detection.
Want to start Deep learning?
Well, to start deep learning you need some pre-requisites. Basic for this is Applied Maths, next starting with Familiarity to python programming. Machine Learning libraries like sci-kit learn and Tensor Flow. Besides these two fundamental prerequisites, you should also know how to train a model and use it.
If you are a beginner, you can start with one of the best courses on Coursera by Andre Ng, A scientist and founder of Google Brain.
You should then start with Deep learning Modern Practices. Note, don’t think like you are now a deep learning expert, you are just starting.
You should focus on – CNNs, Methodology, Linear factor models, and Functions.
So, as we have reached the end of our discussion I hope you have found some valuable information. Along with that, it has been clear what Deep learning is, and how it is being used in daily life. Besides this, we have also looked at some of the examples and found how deep learning is helping and creating advanced systems.