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

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)