What is Machine Learning? Where Is It Used?

What is Machine Learning?

We know humans learn from their past experiences and machines follow instructions given by humans. But what if humans can train the machines to learn from their past data and do what humans can do at much faster pace? Well, that's called machine learning. But it's lots more than just learning, it's about understanding and reasoning. 

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Machine Learning is the field of study that gives computers the capability to learn without being explicitly programmed. 

Machine learning is a branch of artificial intelligence (AI) and computer science which focuses on the use of data and algorithms to imitate the way that humans learn, gradually improving its accuracy.

Misconceptions about machine learning

People have multiple misconceptions on this topic and say that machine learning can insure time travel. 

Machine learning is an important component of the growing field of data science. Through the use of statistical methods, algorithms are trained to make classifications or predictions, uncovering key insights within data mining projects. These insights subsequently drive decision making within applications and businesses, ideally impacting key growth metrics. As big data continues to expand and grow, the market demand for data scientists will increase, requiring them to assist in the identification of the most relevant business questions and subsequently the data to answer them.

How Does Machine Learning Work?

So in machine learning we basically write a programme and then show it the data and train the programme. This makes the programme capable enough to work further on its own. 

We insert huge amounts of data into the machine and it reads the data and judges new things and predicts them as well. 

Suppose a machine is filled with data related to whether of past 3 months like this was a sunny day and this was a rainy day and this is processed by the machine and it tries to understand the data and now if we ask the machine what will be tomorrow's weather, now what machine will do is it will predict the weather with the help of last 3 months data it has and thus this is machine learning and this is how it works.

Hence machine learning is a branch of computer science which learns from its data and predicts new things. These machines try to act like humans.

What are the different types of machine learning?

There are basically 3 types of machine learning presently which includes:

• Supperwise

• Unsupervised

• Reinforcement

Supervised Learning:

Supervised learning, as the name indicates, has the presence of a supervisor as a teacher. Basically supervised learning is when we teach or train the machine using data that is well labeled. Which means some data is already tagged with the correct answer. After that, the machine is provided with a new set of examples(data) so that the supervised learning algorithm analyses the training data(set of training examples) and produces a correct outcome from labeled data. 

Unsupervised Learning:

Unsupervised learning is a type of algorithm that learns patterns from untagged data. Unsupervised learning refers to the use of artificial intelligence (AI) algorithms to identify patterns in data sets containing data points that are neither classified nor labeled. No labels are given to the learning algorithm, leaving it on its own to find structure in its input. 

Reinforcement Learning:

Reinforcement learning is an area of Machine Learning. Reinforcement Learning is a feedback-based Machine learning technique in which an agent learns to behave in an environment by performing the actions. The computer employs trial and error to come up with a solution to the problem. To get the machine to do what the programmer wants, the artificial intelligence gets either rewards or penalties for the actions it performs. Its goal is to maximize the total reward.

Practical Application Of Machine Learning

So where is the machine learning used in our day to day activities? Here is a list to this:

Used in Gmail: There are sections in our gmail like primary, spam etc, but how a particular mail ends up in a particular section this is through machine learning. 

Used By Youtube: Once you watch any video on youtube you will be suggested new videos similar to the one you recently watched now this is not a case in which youtube is smart this is a case of machine learning. Here data mining was used by youtube. Now the user provided a particular interest to youtube and it started finding content on similar topics to make you stick to the app.

Ecommerce Website: Whenever you search for anything or buy anything on any ecommerce website they will be suggesting you similar products or the complementary products you might need and in this way your chances of purchasing more products increases. 

Expert System: Generally this is used in foreign countries as consulting a doctor is chargeable at a higher rate so people prefer using this system in which they can insert their problems and the machine will provide the medicine they can take for this. 

Continued research into deep learning and AI is increasingly focused on developing more general applications. Today's AI models require extensive training in order to produce an algorithm that is highly optimized to perform one task. But some researchers are exploring ways to make models more flexible and are seeking techniques that allow a machine to apply context learned from one task to future, different tasks. If you are looking for one of the best It Companies in India connect with Ozonesoft Solutions.

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