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AIML General Tasks.md
AIML General Tasks.md
 
 
An_introduction_to_Decision_Tree .ipynb
An_introduction_to_Decision_Tree .ipynb
 
 
Classification_of_metrics.ipynb
Classification_of_metrics.ipynb
 
 
Data_Visualization_.ipynb
Data_Visualization_.ipynb
 
 
Implementing_Linear_Regression_from_scratch.ipynb
Implementing_Linear_Regression_from_scratch.ipynb
 
 
KNN.ipynb
KNN.ipynb
 
 
KNN_SCRATCH.ipynb
KNN_SCRATCH.ipynb
 
 
LEVEL 1 FINAL REPORT.md
LEVEL 1 FINAL REPORT.md
 
 
Matplotlib_and_Data_Visualisation(Task 2).ipynb
Matplotlib_and_Data_Visualisation(Task 2).ipynb
 
 
Metrics_and_Performance_Evaluation.ipynb
Metrics_and_Performance_Evaluation.ipynb
 
 
Neural_Networks_and_LLMs.ipynb
Neural_Networks_and_LLMs.ipynb
 
 
README.md
README.md
 
 
Real_world_application_of_Machine_Learning.ipynb
Real_world_application_of_Machine_Learning.ipynb
 
 
Task_3_(Numpy).ipynb
Task_3_(Numpy).ipynb
 
 
logistic_regression_from_scratch.ipynb
logistic_regression_from_scratch.ipynb
 
 
regression_metrics.ipynb
regression_metrics.ipynb
 
 

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MARVEL_AIML

This project aims to cover various topics in Artificial Intelligence and Machine Learning (AIML) through a series of tasks. Each task focuses on different aspects of AIML, including regression, classification, data visualization, mathematical foundations, algorithm implementation from scratch, and exploring real-world applications.

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