The Sparks Foundation (Data Science & Business Analytics Intern)

DATA SCIENCE & BUSINESS ANALYTICS TASKS

TASK-1 : Prediction using Supervised ML

• ABOUT:- Predict the percentage of a student based on the number of study hours
• TASK:- What will be the predicted score if a student studies for 9.25 hours/day
• DATASET:- student_score.csv
• PREDICTION:- If a student studies for 9.25 hours/day, then the predicted score is 93.07% approximately
• PROGRAMMING LANGUAGE:- Python
• TOOLS USED:- Jupyter Notebook and GIT

TASK-2 : Prediction using Unsupervised ML

• ABOUT:- Predict the optimum number of clusters for the given dataset
• TASK:- What will be the optimum number of clusters and represent it visually?
• DATASET:- Iris.csv
• PREDICTION:- Optimum number of clusters for the given dataset is three
• PROGRAMMING LANGUAGE:- Python
• TOOLS USED:- Jupyter Notebook and GIT

TASK-3 : Prediction using Decision Tree Algorithm

• ABOUT:- Create the Decision Tree Classifier for the given dataset
• TASK:- Create the Decision Tree Classifier and visualize it graphically so that when any new data is fed, it would be able to predict the right class accordingly
• DATASET:- Iris.csv
• PROGRAMMING LANGUAGE:- Python
• TOOLS USED:- Jupyter Notebook and GIT

COMPUTER VISION & INTERNET OF THINGS TASKS

TASK-1 : Object Detection/Optical Character Recognition (OCR)

• TASK:- Implement a character detector which extracts printed/handwritten text from an image/video
• RESOURCES:- Computer Vision Methods for Extracting Text from Images
• PROGRAMMING LANGUAGE:- Python
• TOOLS USED:- Jupyter Notebook and GIT

TASK-2 : Color Identification in Image

• TASK:- Implement an image color detector which identifies all the colors in an image/video
• RESOURCES:- Color Identification in Images
• PROGRAMMING LANGUAGE:- Python
• TOOLS USED:- Jupyter Notebook and GIT

AUTHOR

Subham Surana

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