# Student Marks Prediction According to Their Study Hours

This project is based on machine Learning model. which is a Linear Regression Model. It predicts the marks of student according to their study Hours.

I implemented this project by using the machine learning regression model. What is machine learning? So basically machine learning comes under the artificial intelligences. Which focuses on design systems and models by which machines can learn and make decisions and predictions on the experience which is data in the case of machines. Machine learning allows the computer to perform and make the decision by data rather than being explicitly programmed.Artificial intelligence is the wider concept of machines being able to take out the task in a smarter way. AI includes everything which enables for the computer to behave like humans. And as already told you that machine learning the subset of AI. I is based on the idea that we should be able to give data and machine should access the data learn from data and take the decision. Deep learning is comes under the machine learning where the same machine learning algorithms used for the train to deep leaning neural network. I used Anaconda  Jupyter notebook editor for the code which is very easy to use. The examples of machine learning are Tesla’s self-driving car, Apple Siri,  Sophia AI Robot and  many more.

Linear Regression Model:

So regression analysis is the predicting the model which investigates the relationship between a dependent(y) and independent (y) variable, and in linear regression the data is labeled which means machine know the input and output and it gives straight line between x and y which means if the value of x increase then y will also increase.

Libraries

In this project, I used three python libraries pandas, sklearn, matplotlib.

Pandas: pandas library is used to data manipulation and data analysis with panel data same as numpy it also provides a multi dimensional data structure, pandas provide two of data structure single and multi dimension where series is single and data frame is the multi dimensional data structure.by this library we can read csv file where is a data set for the model. It has head(),tail, shape, describe, loc, and iloc method which helps in data analysis.

Sklearn:  For machine learning, Sklearn is the most helpful library in python because it provides so many effective tools for machine learning and it also gives models like classification, regression, clustering and dimensionality. So in this project, I used the linear regression model.

Matplotlib: Machine learning projects have data set with a large amount of data. So every time programmer can not analyze the data so in python by matplotlib library programmer can plot a lot of charts like bar plot, scatter plot, histogram, etc.Matplotlib is also known as a data visualization library. Printing the data: Ploting the graph between Hours and marks: Spliting the dataset into tain and test case: Training the model and printing the values after training the model. Output Screen Shot:

It is predicting the marks by entring the different values of time.      