A company invest lot on employee to train them and make them ready for next generation business. Once you invest in skill enhancement of an employee you need to use it for benefit of business. Employee may be agitated even if they are being paid well as human have aspiration and if aspiration is fulfilled then they perform to their maximum capab…

Machine Learning Algorithms implemented using Numpy and Scipy

Identify hate speech (racist or sexist tweets) in Twitter with NLTK

Data is a Drag: Exploring Classical Machine Learning Algorithms on Small and Imbalanced Datasets

Machine Learning App in R for predicting whether a newly released movie will be a hit or a flop. Practically useful for streaming services and cinemas.

An activity recognizer using a neural network implemented from scratch

na podstawie kursu "Matrix - poznaj reguły gry", stworzonego przez DataWorkshop

In this project we will work with housing data for the city of Ames, Iowa, United States from 2006 to 2010. You can read more about why the data was collected here (https://doi.org/10.1080/10691898.2011.11889627). You can also read about the different columns in the data here (https://www.tandfonline.com/doi/abs/10.1080/10691898.2011.11889627).

This repository contains a Machine Learning model that predicts the comprehensive strength of concrete

Machine Learning Model to automate the loan eligibility

🎓 4th year Artificial Intelligence project. Using the Encog library, it uses vector hashing in conjunction with K-Fold Cross Validation to train a neural network using the WiLI Language Dataset. This neural network can then be used to predict the language of an input.

Data Sampling Library

Handwritten digit recognition using Convolution Neural Network(CNN).

The objective of this repository is to provide a learning and experimentation environment to better understand the details and fundamental concepts of neural networks by building neural networks from scratch.

📔 This repository delves into Logistic Regression for loan approval prediction at LoanTap. It covers data preprocessing, model development, evaluation metrics, and strategic business recommendations. Explore model optimization techniques such as confusion matrix, precision, recall, Roc curve and F1 score to effectively mitigate default risks.

A simple implementation for K nearest neighbor algorithm with k-fold cross-validation.

Build a model using Linear Regression for Banglore Home Prices dataset, then write a python flask server that uses the saved model to serve http requests, then deploy the app to the Cloud(AWS EC2)