https://github.com/jagtaprathmesh19/lgmvip-datascience

https://github.com/jagtaprathmesh19/lgmvip-datascience

Last synced: 24 days ago
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• Host: GitHub
• URL: https://github.com/jagtaprathmesh19/lgmvip-datascience
• Owner: jagtaprathmesh19
• Created: 2021-07-27T05:39:22.000Z (over 3 years ago)
• Default Branch: main
• Last Pushed: 2021-09-08T05:27:01.000Z (over 3 years ago)
• Last Synced: 2024-12-07T18:32:19.498Z (about 1 month ago)
• Language: Jupyter Notebook
• Size: 2.73 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# LGMVIP-DataScience

## Task 1

1) Iris Flowers Classification ML Project :

This particular ML project is usually referred to as the “Hello World” of Machine Learning. The iris flowers dataset contains numeric attributes, and it is perfect for beginners to learn about supervised ML algorithms, mainly how to load and handle data. Also, since this is a small dataset, it can easily fit in memory without requiring special transformations or scaling capabilities.

Datasetlink : http://archive.ics.uci.edu/ml/datasets/Iris 

Output :

| Algorithm          | Accuracy |

:-|-|

| LogisticRegression |  0.95    | 

| Decision Tree      |  0.92    | 

| KNN                |  0.92    | 

| SVM                |  0.89    | 

Result :

Analyzing the different Supervised Learning models, ***Logistice Regression*** is the best model with accuracy of 95% than the decision tree and knn model with 92%.

## *Task 04*

4)Image to Pencil Sketch with Python:

We need to read the image in RBG format and then convert it to a grayscale image. This will turn an image into a classic black and white photo. Then the next thing to do is invert the grayscale image also called negative image, this will be our inverted grayscale image. Inversion can be used to enhance details. Then we can finally create the pencil sketch by mixing the grayscale image with the inverted blurry image. This can be done by dividing the grayscale image by the inverted blurry image. Since images are just arrays, we can easily do this programmatically using the divide function from the cv2 library in Python.

Program Link : Task 4/Task 4 Image to Pencil Sketch with Python.ipynb