Data Science : Admission Prediction using Machine Learning
Data Science : Admission Prediction using Machine Learning
Duration: 40m | .MP4 1280x720, 30 fps(r) | AAC, 44100 Hz, 2ch | 302 MB
Genre: eLearning | Language: English
Duration: 40m | .MP4 1280x720, 30 fps(r) | AAC, 44100 Hz, 2ch | 302 MB
Genre: eLearning | Language: English
A practical Data Science Hands-on Guided Project on Graduate Admission Prediction Using Machine Learning
What you'll learn
Using AI and Machine Learning to Predict Chance of Admit into Universities
Building, Training, Testing and Evaluating Machine learning Models
Learn to create heatmaps, correlation tables, scatter plots and distplot using Seaborn library
A-Z step by step guide into importing libraries, importing and exploring datasets, building a Machine learning model, training, testing and evaluating it.
Learn to work with Linear Regression Machine Learning Algorithm to create Machine Learning Models with approx 96 percent accuracy.
Importing, Exploring and Analyzing datasets and finding correlation between its variables
Requirements
Very basic knowledge of python and its libraries
Description
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.
Who this course is for:
Anyone who wants to build a Machine learning Model and evaluate its prediction
Anyone interested in Data science
More Info
Data Science : Admission Prediction using Machine Learning
