Machine Learning Basics | Introduction to Machine Learning | What is Machine Learning | Machine Learning

 Machine Learning

                         You have seen How rapidly technologies are changing and developing in this digital era and Machin Learning is one of them, You might have come across machine learning too many times. Even if we Consider Facebook, Instagram, YouTube, all these social media apps use machine learning to process and understand users' data, like what is user interest, Which type of ads, and content users like to watch. also, you might have come across weather detection applications or apps, these applications also use machine learning to predict the weather.

                           So let's start with the scientific definition of Machine Learning.

Machine Learning Definition

                                                            As the name suggests, the ability of machines to learn from their past experience without being explicitly programmed. Machine Learning gives the ability to the machine to learn from their past experiences like humans. 

What is Machine Learning?

                                                     We have discussed the definition of Machine Learning at the above point. The machine uses some algorithms to learn  ( Algorithm- the algorithm is a  set of programs). You would have seen on YouTube we get notifications related to our past searches so How does it happen?. It happens because YouTube has its Machine Learning algorithm that tracks your search history and gives notifications related to your past searches. Due to Machine Learning YouTube and other platforms can give us a personalized experience. It is hard to think of this Digital World without Machine Learning. The codes for Machine Learning are generally Programmed in Python Language. Machine Learning reduces difficulties in handling a big amount of data. 

How does Machine Learn?

                                                  Now we know that machines can learn from their past experiences so there should be some way through machine learning. There are three ways to machine learning.                                               

                      1) Supervised Learning

                      2) Unsupervised Learning  

                      3) Reinforcement Learning                               

                    

                These are the three ways through which machines can learn.

1] Supervised Learning

                                        In supervised learning, Machine uses labeled data to predict. Labeled data means both labels and features are provided to the machine so the machine can predict easily with less time.

Suppose use have provided some data to the machine through the program (Algorithm) like if the object weight is 1 kg then it is iron if object weight is 2kg then it is steel and if objects weight is copper then the machine can easily detect object name by their respective weights. So this is all about Supervised Learning.

                                         

  2] Unsupervised Learning 

                                              Machine Learning without labeled data is called Unsupervised learning, Here labeled data is not provided to the machine so Unsupervised Machine Learning uses the prediction method. 

                                            Suppose we want to predict the right rent price for your house, then we will provide information about rents in our area to the machine. the price of rent varies based on the location of the house and the total area of the house.  so we will also have to provide location information of the house to the machine. Based on input information machine can predict the right rent price for our house.

3] Reinforcement Learning 

                                             Reinforcement Learning is reward-based learning which works on the principle of feedback. it takes feedback from the user after giving a prediction. We have seen if we purchase something from a store sometimes they get feedback from us. and based on feedbacks decides the customer liked the product or not. Like these machines use feedback to predict correctly.

If you want to make your career in Machine Learning you should learn some programming languages like python, R, and javascript.

Some best Machine Learning algorithms you should know-

• Linear Regression
• Logistic Regression
• Naive Bayes
• Classification and Regression Trees
• Support Vector Machines (SVM)
• Learning Vector Quantization (LVQ)

If You want to explore Machine Learning more you can refer below videos.

• https://youtu.be/lsf060bLH_Y
• https://youtu.be/bfmFfD2RIcg
• https://youtu.be/GwIo3gDZCVQ
• https://youtu.be/7eh4d6sabA0