Would you like to learn how to predict Chance of Admission into Graduate School using Machine Learning?
Have you ever desired to build a Machine Learning Model?
If the answer to any of the question is “YES”, then you will love this project.
This is a Practical Hands-on Machine Learning Guided Project. You learn by Practice. No unnecessary lectures. No unnecessary details. Direct to the point.
Enrol Now and let’s build a Machine Learning Model together in under 1 hour. We will build a Machine Learning Model and we will feed the data of thousands of students and their GRE Score, TOEFL Score, CGPA, SOP. LOR, University rating and Research to the Model and train it in order to predict the Chance of Admit to Graduate School. In the end, we will test the model and evaluate its performance.
When you complete the project, you will be proud of yourself on what you have learned and achieved.
You will learn more in this one hour of Practice than hundreds of hours of unnecessary theoretical lectures. Learn the most important aspect of Data Science :
Importing all the necessary Libraries
Importing and Exploring Datasets
Building a Linear Regression Machine Learning Model
Training, Testing and Evaluating the model
We will build a Machine Learning model to predict Graduate Admissions. In this hands-on project, we will complete the following tasks:
Task 1: Brief theoretical information about Libraries, Dataset, Linear Regression Algorithm and Google Colab Environment
Task 2: Importing all the necessary Libraries
Task 3: Importing the Graduate Admission dataset to the Colab Environment
Task 4: Data Cleaning: Removing unnecessary columns
Task 5: Exploratory Data Analysis using graphs: Correlation & feature selection
Task 6: Splitting the Dataset into Training and Testing sets
Task 7: Building and Training Linear Regression Model
Task 8: Performance evaluation & Testing the model
Make a leap into Data science with this Hands-on guided project and showcase Machine Learning skills on your resume.
So, grab a coffee, turn on your laptop, click on the “Enrol Now” button and start learning right now.
If you have any questions, or if you want to become part of our team