Science is progressing a lot in today’s present era. From laptops to big technologies like Artificial Intelligence, Biotechnology all is because of science. Science has played a major role in the development of human society. The computer is one of these amazing discoveries that has influenced almost every field of human life. Machine’s time is about to come in time and you can say that it has started. Now machines can think and understand like humans. So how is it possible? Only because of Machine Learning and its applications.
Table of Contents
Machine Learning
Machine learning is a part of artificial intelligence that enables systems to learn automatically and improve upon themselves if needed. Machine learning explicitly teaches automated learning to a system. This makes the system so efficient at performing tasks. The machine can work on itself in the next operation based on its previous experiences and continuously improve that function.
As done by human beings who learn something from all their good and bad experiences. In the future, based on those experiences, make a decision. The concept of machine learning is built on this basis.
Machine learning focuses on the development of computer programs that can access the data on their own and later use it for their learning.
The main reason for making machine learning techniques is that computers can learn on their own without any human help. It can perform tasks better based on instruction and experience. In this, a computer is programmed in such a way that it can work according to the user. It can save the user’s command and the data associated with it.cr
How does Machine Learning work?
Machine learning is a form of artificial intelligence that allows computers to think almost like humans. As it learns from past experiences and improves them. It works by identifying data search patterns. It involves minimal human contact. A big part of what makes machine learning valuable is its ability to detect if a mistake has been made while collecting data.
The process of machine learning starts with data and observation. In this, the machine decides the received data better through direct experience and instruction. These learning techniques are capable of capturing complex analyses that become undefined during human analysis.
Machine learning mainly takes a decision based on three types of functionalities. These functionalities are:
- Decision Process
- An Error Function
- Model Optimization Process
Decision Process
In this process, a machine learning algorithm is used to make some kind of prediction and classify a process. It is levelled based on some input data. The machine learning algorithms infer the patterns present in the data.
An Error Function
It evaluates the prediction made on a model. If sufficient data is available related to the model, it can then compare the data to estimate the accuracy of the model.
Model Optimization Process
Through this process of machine learning, the machine iteratively trains a model and evaluates the maximum and minimum function of the model. This process of machine learning gives better results than other processes.
Types of Machine Learning
There are four types of machine learning algorithms in general.
- Supervised Learning
- Unsupervised Learning
- Semi-Supervised Learning
- Reinforcement Machine Learning
Supervised Learning
In this type of algorithm, the machine applies what it has learned from its past experiences to new data. So that it can work in some way based on the examples given earlier to predict future events.
Different examples are given as input to the machine in supervised learning. This algorithm learns from these examples and estimates the correct output based on the input.
Unsupervised Learning
In Unsupervised Learning, various examples and answers are not given as input to the machine in advance. Algorithms have to guess based on the data itself. Hence this algorithm learns from test data or real data, those not already labelled or categorized.
The Unsupervised Learning algorithm identifies similarities in the data and outputs each new piece of data based on the presence or absence of such similarities.
Semi-Supervised Learning
The algorithm falls between both supervisor and unsupervised algorithms. It uses both labelled and online unlabeled data for training. The system that uses this learning algorithm can periodically improve its training tasks.
Reinforcement Machine Learning
It interacts with its surroundings by presenting actions and discovering errors. Detecting an error is the speciality of this algorithm. This method helps the machine software agent detect the instruction activities of any machine on its own to improve the machine’s tasks.
Application of Machine Learning
Nowadays technology is developing day by day in which machine learning has played an important role. Due to this, there has been a rapid increase in the developments of technology and other important developments. At present, some applications of machine learning are being used a lot by us to make our lives simple and accessible, such as Google Maps, Google Assistant, Alexa, Siri, etc.
Some real-world applications of machine learning are as follows.
Image Recognition
Image recognition is one such important application of machine learning using which an artificial intelligence system can identify digital images of any kind of objects, persons, places, etc.
Speech Recognition
Speech Recognition is an application of machine learning in which voice instructions are converted into text. This is commonly known as speech-to-text. Currently, Google Assistant, Cortana, and Siri are important examples of speech recognition that use speech recognition to follow voice instructions.
Traffic Prediction
At present, travelling to any new place has become very easy and accessible through Google Maps. We can trace our position as well as track traffic.
Users of applications like Google Maps are playing an important role in using these applications as well as making them even better. It takes information related to it from you and uses it as compared to data for better use.
Product Recommendation
To make the customers aware of a product and by making them aware of the usefulness of the product, again and again, the selling of a product is increased. It is being used by various types of e-commerce, companies related to Daily Needs, and entertainment companies.
Whenever you do some search on any social site or Google, after some time you start seeing ads related to it. This is possible only because of machine learning. The suggestions based on your interest in the home page of YouTube are possible only due to machine learning.
Self-Driving Car
A self-driving car is one of the most interesting applications of machine learning using which a driver is not required to control a vehicle. It automatically identifies other vehicles, and persons running on the road and makes you enjoy a safe journey.
Personal Virtual Assistant
Due to the development of science and technology, today we have many types of personal virtual assistants that help us to find related information for us using our voice instruction. It is a type of general personal virtual assistant that can perform common tasks for us like playing any kind of music, calling someone, performing a specific action like opening an email, setting an alarm, scheduling an appointment, etc.
The personal virtual assistant records the voice instructions that we give and sends them to their cloud. Then machine learning decodes this instruction and after that, you get the answer to that instruction.
Medical Diagnosis
The use of machine learning has made it possible in the medical field to diagnose many infectious diseases with greater accuracy, especially those related to the brain. With the help of this technology, a 3D model of the brain can be made, and brain tumours and other diseases related to it can be easily detected and treated.
Stock Marketing Trading
In the stock market, which there is always a risk of volatility in the shares related to any industry. Machine learning is used to make predictions on the stock of industries with the least risk of loss on the market with the help of Long Term Memory Neural Networks.
”Also, its use should be promoted in the right place in the right way.”
Benefits of Machine Learning
The advantages of machine learning have made human life much easier and more accessible. Machine learning is being used to improve tasks in various fields. For this machines are being continuously made more effective and efficient.
- Google is using many new techniques like Google Translate. It detects all the words in it by taking pictures of signs on the road. Translates your language at the same time as it. You can speak anything from Google Translator and the speaker speech recognition working through machine learning will start its work. So that it can recognize the language you have spoken using speech recognition.
- Machine learning is being used in other places like Facebook, shopping websites, and e-mail. Facebook is used a lot around the world. Machine learning is being used in large quantities on Facebook for automatic friend tagging suggestions.
- Based on the best detection and image recognition, Facebook checks its database and recognizes any photo or image. You must have seen that when you search online, the information about the product you searched for is visible to you everywhere like you searched for a product on Amazon. After that when you use Facebook or YouTube then from that product. So you get information related to that product in the form of advertisements etc. All this is possible due to machine learning in which Google monitors all your activities and shows you ads accordingly.
- When you use email, you see that emails arrive in your inbox and others go to your spam folder. This has been also possible due to machine learning. It can detect the content and trace the email. If anything is found wrong it sends the email to the spam folder.
- Its use is not limited to one area but is used in almost every area, such as in sales, where future sales can be predicted. Based on the browsing behaviour of the customer, the appropriate products can be shown to them, thereby increasing the customer experience.
- To enable and increase sales, machine learning is being used in the finance sector as well. It is continuously giving better and faster service to the customer such as increasing transaction security and prohibiting fake activities.
Summary
Machine learning is a rapidly evolving field that has the potential to transform a wide range of industries and applications. It involves the use of algorithms and statistical models to enable computers to learn and make decisions without explicit programming. Machine learning algorithms can be trained on large datasets to recognize patterns and make predictions or decisions.
Machine learning has been applied in a variety of fields, including healthcare, finance, marketing, and manufacturing, to name a few. It has the potential to improve efficiency, reduce costs, and make data-driven decisions.
However, machine learning also raises several ethical and societal concerns, including issues related to privacy, bias, and transparency. It is important that the development and use of machine learning technologies be guided by ethical considerations and that their potential impacts on society are carefully considered.