https://github.com/akashkobal/data-science

I'm excited to share my data science project🚀, where I've applied various techniques and insights to solve a specific problem. The project follows best practices for maintainability and reproducibility, using the Data Science Project Template. Dive into the project to explore the code, datasets, documentation, and resources that showcase MyJourney
https://github.com/akashkobal/data-science

akash akash-kobal akashkobal applied-data-science artificial-intelligence classification data-science dataanalysis dataanalytics datascienceproject datascientist deep-learning kobal machine-learning prediction regression

Last synced: 6 months ago
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I'm excited to share my data science project🚀, where I've applied various techniques and insights to solve a specific problem. The project follows best practices for maintainability and reproducibility, using the Data Science Project Template. Dive into the project to explore the code, datasets, documentation, and resources that showcase MyJourney

• Host: GitHub
• URL: https://github.com/akashkobal/data-science
• Owner: AkashKobal
• License: mit
• Created: 2023-09-25T18:10:48.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2024-04-13T05:00:23.000Z (almost 2 years ago)
• Last Synced: 2024-04-14T16:14:06.119Z (almost 2 years ago)
• Topics: akash, akash-kobal, akashkobal, applied-data-science, artificial-intelligence, classification, data-science, dataanalysis, dataanalytics, datascienceproject, datascientist, deep-learning, kobal, machine-learning, prediction, regression
• Language: Jupyter Notebook
• Homepage: https://theakash.co.in
• Size: 54.2 MB
• Stars: 7
• Watchers: 3
• Forks: 6
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

          
# Data-Science 

1) Python

2) Jupyter Notebook

3) Numpy

4) Pandas

5) Matplotlib for data visualization 

6)  Machine Learning using sklearn

7) Deep learning using tensorflow 2.0 

 

Data Science Project

  

1. Big Mart Sales Prediction
 

2. Credit Card Fraud Detection
  

3. Mashroom Classification
 

4. Iris Prediction


5. Heart Disease Prediction
  

6. Stock Price Prediction


 Machine Learning

1. Linear Regression Single Variable


2. Linear Regression Multiple Variable


3. Gradient Decent and Cost Function


4. Save Model Using Joblib and Pickle


5. Dummy Variable and One Hot Encoding


6. Training and Testing Data


7. Logistic Regression (Binary Classification)


8. Logistic Regression (Multiclass Classification)


9. Decision Tree


10. Support Vector Machine (SVM)


11. Random Forest


 Deep Learning



1. [Potato Disease Classification](https://github.com/AkashKobal/potato-disease-classification.git)