Do you remember unlocking your mobile phones with that difficult patterns or pins, so that nobody could have access to your mobiles? Or doing everything by your self from setting an alarm to making a call?
But now a drastic change has come, your mobile uses the front camera to recognize you and unlocks your phone without any efforts to remember or enter the password, you have "SIRI" and "ALEXA" that does things when you instruct them, your emails are going in your spam folder automatically and many more. The main thing behind all of this is MACHINE LEARNING(ML).
What comes to your mind when you hear the word machine learning? A machine that is learning, right? Yes, it's something like that only, when a machine learns from the examples and accordingly performs on new ones. Remember, being a kid and preparing for the mathematics exam by just solving the questions in your book, similarly our computer learns from the data that we provide to it just like you did from your mathematics book and it tries to perform on new ones as you did in your exam.
Technically, machine learning is a subset of Artificial Intelligence (AI) which provides systems with the ability to learn and improve automatically from experience. It focuses on creating computer algorithms that can access data and use it to learn for themselves. The learning process starts with observations or data, such as examples, direct experience, or feedback, to search for trends in the data and make decisions in the future on the examples we provide to it. The primary objective is to allow computers to automatically learn without human interference or assistance, and to adapt behaviour accordingly.
Data - Just like food is really important for us similarly data is the basic necessity of machine learning models. The more diverse data you provide to your computer, the better will be the results.
Features - Consider this, what do you check before buying a laptop? It's features like brand, battery, RAM, storage and many more. But from where did you buy the laptop or who was the salesperson of the store, do you consider these? No, right? That is what choosing the right features is and it's also the main source of errors in our ML models.
Algorithms - This is the most obvious part. These are engines of machine learning, meaning it is the algorithms that turn a data set into a model.The method you choose finally affects the precision, performance, and size of the model.
Machine learning is one modern innovation that has helped man enhance not only many industrial and professional processes but has also advanced our everyday living. It is present all around us.
Few examples are mentioned below:
- Image Recognition
- Medical diagnosis
- Online Customer Support
- Product Recommendations
- Speech Recognition
- Virtual Personal Assistants
- Email Spam and Malware Filtering
- Fraud Detection
Two of the most widely adopted machine learning methods are supervised learning and unsupervised learning, but there are also other methods of machine learning like reinforcement and semisupervised learning.
- Supervised Learning - It is used when we provide input data as well as correct output data to the machine learning model. The algorithm learns by comparing its actual output with correct outputs to find errors. It then modifies the model accordingly.
- Unsupervised Learning - It is used when the information used to train our machine learning model is neither classified nor labeled. The algorithm explores the given data and finds some structure within.
Most industries working with large amounts of data have recognized the value of machine learning technology. By using this the organizations are able to work more efficiently or gain an advantage over competitors. Few sectors using machine learning are mentioned below:
- Financial Services
- Health Care
- Oil and Gas
Imagine you are just sitting idle and you have someone who is doing your work, though it isn't good for our health, but yes it amazes us. Soon the robots will take over most of dangerous jobs such as welding and bomb disposals. We will have self driven cars that uses machine learning to check for the surroundings and move accordingly. Crazy! Right?
In conclusion we can call our future as "An Automated World" and this all will be possible because of Machine Learning.