Have you ever desired to build, train and test a Machine Learning Model in a real-world application?
Would you like to learn how to predict Chance of Admission into Graduate School using Machine Learning?
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 with a real-world application of Machine learning. You learn by Practice. No unnecessary lectures. No unnecessary details. Clear, Concise, to the point Course.
By the end of this course, you will be confident in building. training and testing any Linear Regression Machine Learning Model and Implementing them in real-world scenarios.
No prior Experience in Machine learning required. We will guide you from first to last: Every Single Step.
"Gosh, this was fast! I was so absorbed with the learning I did not even realise I went through it no-stop! Really, interesting, the material is well done and presented in a concise but very clear manner. Surely the course is short but is lacking of nothing, I am in ore and full of praise! Well deserved 5 stars!"
"This Course is very great to learn Machine learning & Data Science."
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.