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AI-ML-Data-Science-Practice

This repository contains codes related to my AI , Machine learning and data Science practice for courseworks and self learning.

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├── Hackerrank_solved_problems
│   ├── Artificial_Intelligence
│   │   └── hackerrank_polynomial_regression_office_price_prediction.py
│   └── Python
│       ├── Class
│       ├── Debugging
│       ├── Error_and_exception
│       ├── Math
│       ├── Numpy
│       ├── Regex
│       ├── Strings
│       └── XML
├── LICENSE
├── ML_practice
│   ├── README.md
│   ├── Supervised_Learning
│   │   ├── 01_Linear_Regression
│   │   ├── 02_Logistic_Regression
│   │   ├── 03_K_Nearest_Neighbour
│   │   ├── 04_Naive_Bayes
│   │   ├── 05_Support_Vector_Machine
│   │   ├── 06_Decison_Tree
│   │   ├── 07_Ensemble_Methods
│   │   └── data
│   └── Unsupervised_Learning
│       ├── 01_Clustering
│       ├── 02_Dimensionality_Reduction
│       ├── 03_Anomaly_Detection
│       └── data
├── MSCSE_Coursework
│   ├── Advanced_AI
│   │   └── Optimization_and_Evolutionary_Algorithms
│   ├── Data_Mining
│   │   ├── Rainfall_Predict
│   │   └── bd_lifexp_gdp.ipynb
│   ├── Financial_Informatics
│   │   └── house_price_prediction.ipynb
│   └── Machine_Learning
│       └── StackOverflow_Question_Tag_classification.ipynb
├── Natural_Language_Processing
│   ├── LSTM_text_generation_using_Adele_dataset.ipynb
│   └── nlp_libraries.ipynb
└── README.md
└── requirements
    ├── conda_requirements.txt
    └── pip_requirements.txt