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In this blog, we will learn about what is Machine Learning in simple words? machine-learning methods, why it is important, and the applications of machine learning.
So before learning about machine learning you should firstly know about what is the difference between machine and human. So first, we will learn the difference between humans and machines, after that we will learn about what is machine learning?

➢The Difference Between Machines And Humans:-

                      The difference between computers or machines and humans is that humans always learn from their past experiences, at least human try, but computers or machines need to be told what to do.
knowledge processing machines are solid tests, reasoning machines with zero common sense, That means if we want them to do something that means if we want to order the machine, we have to provide them step-by-step instructions on exactly what to do and all detailed related with what to do exactly.
for this, we write programmed and scripts computers to follow those instructions. That is where Machine Learning comes in. In the machine learning Concept which is consists of getting computers to learn from experiences-past data.

What Is Machine Learning?

Machine learning is the method of the data analysis that automates analytical model building. It is a branch of (AI) artificial intelligence that is based on the concept that systems can learn from identifying patterns, data, and make the decisions with minimal human intervention. 

In short, we can say that MI is Machine Learning which is an application of AI that is an artificial intelligence that provides systems or the computer's ability to learn and improve automatically from the experience without being directly programmed. MI(Machine Learning) focusing on the development of computer programs that can access the data and use it to learn for themselves.
The process of learning starts with the observations of the data(examples is instruction or direct experience), in order to look for patterns in data and make better decisions in the future based on the examples that we provide. The important thing is to allow computers or systems to learn automatically without human intervention or assistance and adjust actions accordingly.

Machine learning gives the computer the ability to learn without being programmed explicitly. The important point of machine learning is to provide algorithms that are trained to perform a task.
It is related to the field of mathematical optimization and computational statistics.

Machine learning has 4 methods, which are supervised learning, unsupervised learning,semi-supervised learning, and reinforcement learning, each with its own use cases and algorithms.

Types Of Machine Learning:-

  • Supervised Learning
it is a method in which we teach to  the machine or computers using labeled data
  • Unsupervised Learning
The machine is trained on unlabeled data without any guidance
  • Reinforcement Learning
it is an agent interacts with its environment by producing actions and discovers errors or rewards

Why Machine Learning Is Important:-

our word is gradually evolving to become more technology-reliant. and one technology expected to revolutionize the future is machine learning. from  unimportant jobs to sophisticated services, everything today is using machine learning
 the world is slowly but surely is moving toward Machine Learning to become more reliant.
Google or Facebook and many more are now heavily embedded around the Machine Learning.

Applications Of The Machine Learning:-

  • Virtual Personal Assistants
some of the popular examples of virtual personal assistants are Siri, Alexa, Google, they assist in finding information when asked over voice.
Machine learning(ML) plays the main role in these personal assistants as they collect and refine the information on the basis of your previous involvement with them. 
  •  Predictions while Commuting
now we are using GPS navigation services. it shows our current locations and velocities are being saved at a central server for managing traffic. This data is then used to build a map of the current traffic. While this helps in preventing the traffic and does congestion analysis, the underlying problem is that there are fewer cars that are equipped with GPS. Machine learning helps to estimate the regions where congestion can be found on the basis of daily experiences.
ML is playing a major role when we book online cabs/cab, it estimates the price.
  • Videos Surveillance
nowadays The video surveillance system is powered by AI and because of this it possible to detect crime before they happen. The system can thus give an alert message to the human attendants, which helps to avoid mishaps. 
  • Social Media Services
Because of Machine learning, the quality of photos videos are automatically enhanced, machine learning detect the spam content and bad backlink also because of this it provides the security 
  • Email Spam and Malware Filtering
machine-learning detect the spam messages, threats and malware and because of this it provides security
  • Online Customer Support
machine-learning provides the number of websites to chat with customers to give him better service.
  • Search Engine Result Refining
search engines like google use machine learning to improve the search results for you
  • Product Recommendations
You shopped for a product online and after a few days you keep receiving emails for shopping suggestion, this is happened because of machine learning
  • Online Fraud Detection 
Machine learning is proving it's possible to make cyberspace a secure place and tracking monetary frauds online is one of its examples.

 How To  Become A Machine Learning Expert:-

  • Understand the basics like general knowledge about the field.
  •  Learn some Statistics.
  •  Learn Python or R  for data analysis<you can learn both languages also>. 
  • Complete an Exploratory Data Analysis Project
  •  Create unsupervised learning models
  • Create supervised learning models
  •  Understand Big Data Technologies
  •  Explore Deep Learning Models
  • Undertake and Complete a Data Project


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