Machine Learning Project End to End: Student Mark Prediction

This is an end-to-end Machine Learning/Data Science Project. We start the project from business problems to deployment on the cloud.

Student Mark Prediction – Complete Machine Learning Project


10th ( Pass / Failed)

Should Know Hindi


Not need to install S/W

Need Gmail ID

Mobile or Laptop

Machine Learning Projects Gurney

We covered all the below steps in this project in detail.

Business Problem

Get The Data

Discover and Visualize the Data to Gain Insights

Prepare the Data for Machine Learning Algorithms

Select a Model and Train It

Fine-Tune Your Model

Present Your Solution

Launch, Monitor, and Maintain your system

Below is Jupyter Notebook file to download with practical and prime video tutorial link.

Student Mark Prediction ML Project Deployment on Cloud AWS EC2

Download below rar file of above project.

Amazon AWS >>> Click Here

PuTTY >>> Click Here

WinSCP >>> Click Here

7 Replies to “Machine Learning Project End to End: Student Mark Prediction”

  1. Hello Sir, I had learned more concets from here but I have one poroblem arise while applying simple linear Regrssion algorithm. This problem mentioned below please sir tell me why this error occurs and where my mistake is?
    My problem:,y_train)

    ValueError: Found input variables with inconsistent numbers of samples: [24, 6]

    1. there must be some problem during train_test_split part of your code. Make sure that your X_train and y_train should have same size.

      (Correct Code)–> X_train,X_test,y_train,y_test= sklearn.model_selection.train_test_split(X,y,test_size=0.2)

      1. X_train, X_test,y_train,y_test = train_test_split(X,y, test_size = 0.2, random_state=51)

      2. X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=51) this way you can split don’t need to write this sklearn.model_selection you can directly start..hope this will helpful for you.thank you

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