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bench-mark-of-svm-knn-dt-and-cnn-on-xrd-dataset

data-for-pervoskite-solar-cell

exporting-a-train-model

When you attain the desired accuracy of a model the next is how to use it later.

house-price-prediction

House-price-prediction

images-processing-with-opencv

A GitHub repository for image processing and segmentation algorithms, models, and datasets, enabling research, development, and practical applications in computer vision and medical imaging.

language-model-from-scratch

map-method-to-map-the-dictionary-with-pandas-column

This code snippet contains map method to map the dictionary values to the pandas column categories.

model_flask_deployment

This project demonstrates the deployment of machine learning models using Flask, a lightweight web framework for Python. The goal is to showcase a simple yet powerful way to turn your trained models into interactive web applications.

natural-language-processing-with-nltk

A GitHub repository for Natural Language Toolkit (NLTK), providing a comprehensive suite of libraries and resources for natural language processing tasks.

news-share-app

one-hot-encoding-of-most-frequent-category.

function for one hot encoding of most frequent categories in pandas column.

slot-machine-game

In this project I create a slot machine game. Where player can bet on lines of slot machine for character matching . If character matches on a line or lines, player will get reward.

text-sentimentanalysis-hf-bert

wine-knn-classification.

Wine dataset has 177 data samples and 3 labels. We train the dataset using KNN model which find the Euclidian distance between the new test data sample and all the samples of training data. Based on the distance and number of nearest neighbors selected we sort the distances with minimum values. If majority of the sorted distance values belong to one specific class we then we put new test sample into that specific class. In this way we classify the whole test dataset and check the prediction of the model.