On this auspicious day of New Year (2080) Hindhu Sambat and Odia calendar Wishing you all a Happy New Year

This repository contains basic implementation of supervised learning approaches

1. Gaussain Naive Bayes 2. KNN 2. Decision Trees 4. MLP

The softwares required for this application

1. Python 3.X
2. Numpy Library
3. Pandas Library
4. Scikit-Learn

Python already installed (Ubuntu 18.04)

conda commands for installing those libraries

1. conda install numpy
2. conda install pandas
3. conda install scikit-learn
4. conda install matplotlib
5. conda install python-graphviz
6. conda install pydotplus

Chapter-1

in Intro-5.2-1 note - [ a1 0 0 , 0 a2 0, 0 0 a3 ] -----> corrected matrix 3x3 You are not studying properly ! !!!!!!!!

#SULE(Supervised LEarning)

The dataset file and jupyter notebook file

1. fruit_data.csv
2. SULE.ipynb

Chapter-6

Reinforcement Learning

1. NEAT simulation

Chapter-7

Generative Networks - Generative Adversial Networks

Dataset - GOogle drive link will be shared Reference -Kaggle

Python course for machine learning will be there after sometime

Copyright (c) 2023, 2024 Radhamadhab Dalai, ITER , Siksha O Aanusandhan University, Odisha, India Author's email address : [email protected]