https://github.com/amey-thakur/tsf-supervised-machine-learning

Task: To predict the percentage of a student based on the number of study hours.
https://github.com/amey-thakur/tsf-supervised-machine-learning

amey ameythakur deep-learning machine-learning matplotlib matplotlib-pyplot numpy pandas python python3 seaborn the-sparks-foundation tsf

Last synced: about 2 months ago
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Task: To predict the percentage of a student based on the number of study hours.

• Host: GitHub
• URL: https://github.com/amey-thakur/tsf-supervised-machine-learning
• Owner: Amey-Thakur
• Created: 2021-07-02T10:56:23.000Z (over 3 years ago)
• Default Branch: main
• Last Pushed: 2024-03-13T17:31:31.000Z (10 months ago)
• Last Synced: 2024-05-14T00:23:40.632Z (8 months ago)
• Topics: amey, ameythakur, deep-learning, machine-learning, matplotlib, matplotlib-pyplot, numpy, pandas, python, python3, seaborn, the-sparks-foundation, tsf
• Language: Jupyter Notebook
• Homepage: https://www.youtube.com/watch?v=qsO9GyGNWf0
• Size: 192 KB
• Stars: 8
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# THE SPARKS FOUNDATION - SUPERVISED MACHINE LEARNING

 >**TSF - SUPERVISED MACHINE LEARNING TASK - 1**

 

 - **[YouTube Video](https://www.youtube.com/watch?v=qsO9GyGNWf0)**

 

 - **[Google Colaboratory](https://github.com/Amey-Thakur/TSF-SUPERVISED-MACHINE-LEARNING/blob/main/TSF_INTERNSHIP_TASK_1_SUPERVISED_LEARNING.ipynb)**

 

 - **[Kaggle](https://www.kaggle.com/ameythakur20/tsf-internship-task-1-supervised-learning)**

 

 - **LinkedIn Posts - [Submission](https://www.linkedin.com/posts/amey-thakur_connections-task1-thesparkfoundation-activity-6816761779583111168-jROt) | [Completion](https://www.linkedin.com/posts/amey-thakur_connections-gripjuly21-gripjuly2021-activity-6823906924413771776-9XIe)**

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 - **_Task: To predict the percentage of a student based on the number of study hours._**

   - **_Simple Linear Regression is used as it involves just 2 variables._**

   - **_Output: To find predicted score if a student studies for 9.25 hrs/day._**

## TECHNOLOGIES AND LIBRARIES USED:

 

 - Python3, Pandas, Numpy, Matplotlib.pyplot, Seaborn.

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  👉🏻 Presented as a part of the Internship @ The Sparks Foundation 👈🏻  

 

 ✌🏻 Back To Engineering ✌🏻