Machine Learning Algorithms
MLA 

MLA previous year question papers are given at the bottom of this page

Tree diagram of machine learning algorithms

Important Topic For Exam

Machine learning algorithms classifying into three types will be given below

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

1.) Supervised Machine Learning  

In this, the machine needs an external support. The machine is trained using datasets labeled by external support.

After training the machine, a new data or image is given that matches the previous data and the machine is tested to see if the machine actually works to classify the data correctly.

In this machine learning, the main objective is to make a correct mapping between input data and output data

Let's take the example of supervised machine learning, we feed the machine various labeled images of dogs and cats and train the machine with a given dataset, then we feed the machine a new image of a cat to see if the machine actually works, and then the machine operates on that image and the given image In what category does it work? Let's see what happens. First, it will find similarities between a given image and a dataset. Depending on the size, color, eyes, category the machine fits into, the dog or cat will see the image and after checking this it will give the correct output.

Different types of supervised Machine learning

• Regression
• Classification

1. Regression  Analysis :-  There is a company called xyz whose product is sold and we want to calculate the annual sales of that company, but there will be many factors that affect the annual sales, that is, the annual sales become the dependent variable and those factors affect the annual sales. are independent variables. This type of analysis is known as regression analysis.

Regression also classify into types

• Linear regression:- in this type of regression the continuous value is given.
For example, the salary of those who have government jobs increases as the years increase


a)Simple linear regression
b)Multiple linear regression

• polynomial regression

2.calssification :- 

• Logistics regression:- logistics regression are classified into three types

a) Binomial logistics regression :- logistic regression in which categorises responses as either yes or no,

b) multinomial logistics regression

c) ordinal logistics regression

• k-Nearest Neighbors (KNN algorithm)
• Support Vector Machine (SVM) :- 

Let's understand SVM through the above image. If we have a dataset of quadrilateral and circle, then we have to draw a line (hyperplane) that separates the circle and quadrilateral.

SVM also classify into two types 

• Linear SVM :- seperate dataset by straight line 
• 
  
• Non linear SVM:- data not classify by straight line

• Kernel  function :- The kernel function works in this way, it transforms data from lower dimensions to higher dimensions. When a 2D dataset is converted to 3D or converted to a higher dimension, it becomes easier to visualize the data and we can easily separate the dataset.

Low dimensional data 

    |

Kernel function

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Highh dimensional data 

• Naive Bayes :-  Naive Bayes classifier is base on Bayes theorem

Bayes theorem

Probability:- 

• Decision Tree :- In a decision tree, we first create a tree like structure first, which has a main attribute. Then a decision tree is formed, complete with decision node and leaf node. In the exam, there is definitely a question on the decision tree.An example of a decision tree like temperature (main attribute) and its branches (decision node). 1. cold 2. hot 3.mild, then whether the temperature is cold or not. If cold write yes if  then write No (leaf node). All of them make one decision.

2.Unsupervised machine learning

In unsupervised machine learning, there is no lable data. In unsupervised machine learning, the dataset is separated by looking at shape, colour, etc.

An example of unsupervised machine learning is when we bring fruits and vegetables from the market. All the potatoes and tomatoes are grouped together, and then we separate the potatoes and tomatoes. We can do this because of their different colours and shapes. If there is similarity in the dataset, it is divided into one group, and those that do not have similarity are divided into another.

Types of unsupervised Machine learning

• K-means clustering
• Hierarchal clustering
• Principle Component Analysis

 Important Topics For numerical

• Bayes theorem 
• K- mean clusteing 
• K-NN 
• Principle Component Analysis
• Decision Tree 

CAE-2 IMP Topic 

How to download this image ?

Step 1: - First you click on the image

Step 2: - After the first step you will see the image completely clear, then you long press on to the image

Step 3: - After that you will get an option list. In that list click on download image option and your image will start downloading.

step 4: - Click on the cross button in the top right corner to come back 

questions bank 🏦

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CAE-1 2021

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     CAE-2 2021

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Also refer this question paper 

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Artificial intelligence and machine learning algorithms

previous year question paper GHRCE

Artificial intelligence and machine learning algorithms previous year question paper winter ❄️ 2018

Artificial intelligence and machine learning algorithm  previous year question paper winter ❄️ 2018

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For All 2nd year previous year question papers 

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https://classmate2022.blogspot.com/2022/04/blog-post_30.html?m=1

Please share this link with your friends and college group to assist them!

Dear friends, Welcome to my website, classmate2022. My name is Harshad Nichat and I am also studying in the 3rd year AI branch A section at G.H. Raisoni College of Engineering, Nagpur.

 I want to tell you that all the previous year's question papers for the first, second, and third years of G.H. Raisoni College of Engineering, Nagpur have been uploaded. My only purpose behind creating this website or behind uploading the paper is so that everyone can get previous year question papers because I was in 1st year too and I also wanted the paper because, after seeing the previous year question papers, we know the background of that question paper or what type of paper it is. Thus, it helps to know what types of questions will come, and thus your end of semester exam results are good. Another thing is that some questions from previous year's question papers are repeated in your exam, so it is necessary to get previous year's question papers. I am not getting any profit if I do paper work. I am doing paper work only because my hobby is helping others and I am doing it. 

                     If you are also willing to help me, then give me your feedback. How do you like this site? Tell us about what else needs to be implemented in and share the link to this site with your friends and in your group so that everyone can get the previous year's questions paper. Get the papers and, if possible, 

          send me your CAE-1 & 2 END SEM question papers, which will help the students who will take admission next year.