Introduction to Machine Learning

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This is the era of Machine Learning (ML) as increasing the power of computation in computer technologies, and there is a lot of data to manage for each sector in the world. We have lots of data (symptoms, cures) for diseases, economic data (share market, trading) and there is also confidential data that could be used to decide on a business, agriculture, or even in a presidential decision for a country. These are the enormous use of ML, except that there are various small sectors where machine learning is performing well for doing human tasks. 

Machine Learning is a significant branch of Artificial Intelligence (AI). The idea of it is to generate a decision from several earlier examples for a new instance of the same kind of problem or cluster them in several groups.

Machine Learning is divided into three substantial categories, such as – 

  1. Supervised Learning
  2. Unsupervised Learning
  3. Reinforcement Learning

Let’s discuss about these three categories. 

1. Supervised Learning

In this category of machine learning, we want to train the model with some features, and there is class value/values for each instance. Here, 

  1. Features are whatever things we need to express or describe the event/object; it could be size, time, length etc. 
  2. Class value is the thing what we want to predict about the object, like type etc. 
  3. Description of each event/object is an instance.

There are various models/algorithms to solve this kind of problem. However one model is better than other models for different contexts. So here are several machine learning models –

  • Naive Bayes
  • KNN
  • Decision Tree
  • Support Vector Machine
  • Linear Regression
  • Logistic Regression
  • Deep Learning models – Most popular

We will discuss about deep learning in upcoming blog post in elaborately.

2. Unsupervised Learning

Unsupervised learning is the method to group or categories samples. Unlike machine learning, it does not have class values for the instances. Therefore it is mostly used to find previously unknown patterns. There is a couple of algorithms for this category- 

  • K-means
  • OPTICS algorithm
  • Mixture models

3. Reinforcement Learning

Reinforcement learning is the way of a train a model without human interaction. As a result the model learns interactively from the environment. So, when the model gets an event or object, it tries to predict the result that we want. Therefore if the result is correct, the model receives a reward, and if the result is wrong, the model gets punishment. In that way, the model knows what should do next time.

Tools for Machine Learning

There is a lot of tools for developing machine learning with different features and advantages; here, I am sharing the most popular tools. Such as- 

  • Frameworks for Machine Learning: sci-kit learn, PyTorch, TensorFlow, Keras
  • Helper Frameworks: pandas, numpy, matplotlib, seaborn, OpenCV
  • Programming Languages: Python, R, C++

Keep eyes for my next blog- Augnitive Blogs 

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Machine Learning (ML) is a significant branch of Artificial Intelligence (AI) which can be trained on a large number of data to determine patterns. So that it could predict upcoming events of similar type of patterns.

As an instance, if we train a Machine Learning model to detect car license details from images/videos on a large number of image examples, the model could recognize other car licenses too. It can do a lot humanly tasks like providing relevant information/products to interested web visitor, suggest necessary goods and much more.

Recently Machine Learning has become a trend on developing applications including web applications. It would be widely used in web development to get security for websites, get more sales for e-commerce, and visitors could get better experience buying products online. We can see that the Machine Learning will change the way of the sites are now.

Machine Learning in Web Security

Machine Learning can improve securities for websites as it can detect visitors’ behavior based on past data. Based on the visitors’ behavior, it can take actions automatically and instantly. In that case, it can defend lots of web attacks and bad bots for attacking/visiting sites. The best benefit of using machine learning in web security will be taking decision instantly, quickly and automatically.

There is a couple of models already developed to do this kinds of security agents. As an example, some security firms build machine learning models to detect phishing websites.

Best Experience on Selling and Buying Products Online

By using Machine Learning, the web site will be able to determine visitor’s needs, exciting products. So, there will be more sales for the owner as well as visitors could fulfill their needs. In that case, it creates a win-win situation. Imagine, instead of searching or choosing products for a long time, you get an automatic suggestion by Machine Learning that matches your needs. Of Course, it will be good, won’t it?

Machine Learning could help online selling business in various ways like determining the best selling price, best products to sell and a lot. Some big online selling companies already started using Machine Learning to boost their business, like Apple, Amazon, Alibaba etc.

Managing Interesting and Needy Contents

Some prominent social networking companies have already started using machine learning. They are trying to give their users personalized content for each of them. So the users are getting more interested in using their products. As a result they are getting content according to their need and the content as they are interested in. In this case, both parties win again.

Search engines are giving search result with Machine Learning nowadays. Also, it could be used in news provider companies to make the best experience for their news reader.

In conclusion, we can say that Machine Learning is going to make a significant impact on Web Development that we cannot even think right now. It is possible to make the best experience of visiting websites, doing anything on any specific site that solves any problem by using Machine Learning because it will help visitors to do less but get more.

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