Today the world is full of technology, we are not doing anything without technology. From mobile phones to shaving machines, machine learning is based on that. All the digital machines we use around us are based on machine learning. Such as a blogging website. So let's know the areas affected by machine learning? What is machine learning technology?
Machine learning (machine learning) or m. L. (ML) is a type or subdivision of artificial intelligence (artificial intelligence) under computer science, in which any computer is able to automatically acquire new things based on its old experience, data, form and knowledge.
In this sequence, one more word can be seen and heard due to which new people become more and more confused and that is DP learning. In fact, it is nothing but a subdivision of machine learning. The main difference between machine learning and deep learning is that even after training machine learning systems, there is scope to improve and provide new inputs from time to time, on the other hand for DP learning Our system is so. Be able to make any decision by themselves and know about any new things without any input input or updates.
Let me try to understand you in simple words, first of all, a computer, software or learning model (learning model) is prepared by a computer engineer on a special algorithm developed by him and then provides a large amount of basic training input data. We do. Goes. Here any software or machine is made so qualified that once the basic training is complete, this system or model will be followed by any input given such as sentence (sentence), voice (voice), picture (picture) Or are able to give feedback, conclusions or answers on their own based on visuals etc.
When we talk of machine learning, there are two main types of learning or training process.
Supervised learning:- Under this, we can use any computer or model already known (labeled or tagged examples) or pre-directed training data to help us develop the essential rays of the particular machine learning algorithm ( Trained) do. . In other simple words, if we say, we test the computer by presenting some examples. Once our model or computer is tested, it later analyzes it via algorithms by matching the given input or instruction with the preceding example and providing us with the desired material on this basis.
Two types of algorithms are mainly used in supervised learning-
Classification:- In this, the computer divides the input data (raw input data) into several classes. For example, if we try to find out the email through this, here we will use 20 actual emails as computer training data. In which 10 minutes i.e. email are email and 10 are correct. We will tweet these emails as labels or tags (spam) and not (not spam).
Once our computer is paper then when we test this model it will divide the given input into several points and look for possibilities. If the score is 0.9 or higher, it is an email email and if the score is 0.1 or less, it is a correct email.
In the same way we can train our computer for many different things through the classification algorithm, like we will train our machine through some pictures of car and bike, in which we will prove that the car is and the picture is bike . Of. Once our computer completes this training, it now recognizes to a large extent the difference between these two in the photographs.
Regression:- Through this algorithm, the computer is trained to find continuous or unknown numbers through some old data. For example, if we have to assess the value of a person or house on the basis of location, area, age etc., or to find out the Bare Market or Bull Market trends in the context of the stock market. We will train the computer using some old existing data. Once this is completed then our computer will be able to estimate the value of any property or house to a large extent based on these data received. In this, the larger the size of the training data, the more accurate our computer will be able to give the correct answer.
Unsupervised learning:- Under this, we train computers or models with mixed, unknown and unlabeled data input which is not pre-directed and the computer can self-assess through its algorithm to separate all these information. We do. -Classifies (categorized) into different categories. Later on this basis it presents the result or before us.
In Unsupervised Learning, there are mainly two types of algorithms used.
Clustering (clustering):- Under this, the computer divides one type of data or information into different classes. Many different types of clustering techniques are used, with K-Means clustering being considered the most appropriate and effective. In this, different clusters of the same type of data object are first formed. An attempt is then made to reduce the distance between all the objects present in each cluster. There the distance between the second and the object of different cluster is maximized. We try to understand similar things through the picture below.
Association:- Through this, the data collected is collected in different form to find the closest and mutually related results, activities, objects etc. between them. For example, most people who buy bread and butter also buy milk. It is on this basis that companies motivate you to buy their other product. Through this algorithm, search engines like Google also have to offer you some suggestions based on your old searched keywords and act data. The new friends who are suggested to you on Facebook are likewise part of the algorithm.
Machine learning and especially deep learning is a subject of great endowment. It is going to be in great demand in the coming years. It is also my favorite subject, on which my evaluation continues. Here I have tried to explain it in simple succinct language only through thick things. On the basis of machine learning, engineers and scientists today are engaged in developing robots with human appearance and brains, which, like a common man, are able to learn from themselves based on the things, people and activities around them. Are capable. Will be.
Hope this post gives you information that there are areas affected by machine learning? What is machine learning technology? For more information related to technology read our more posts.
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