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.

Progetto di Intelligenza artificiale sugli alberi di decisione con valori mancanti.

Machine Learning Algorithms implemented using Numpy and Scipy

Numerical Methods: "Handwritten Digit Recognition" Group Project - 2nd Semester 2021 - Computer Science, UBA

Insights into how the error varies with change in K while performing k-fold Cross Validation

Experimenting ML Algorithms, feature selection, cross validation and feature transformation on self-annotated custom Eskişehir real estate dataset. - 2021 - Yildiz Technical University

Implementation of Naive Bayes, Gaussian Naive Bayes, and 5-fold cross-validation Nearest neighbor with pure python

GroupSplit is a module to help split datasets into train and test sets for data science and machine learning projects.

Collaborative filtering, word Embedding dense vector representation - NeuralNetwork regression model and K-Fold Evaluation.

Image classification with DeiT model, including data preprocessing, k-fold CV, early stopping and model saving.

This repository consists of 6 sections, detailing hands on Machine Learning Models: Regression, Classification, Clustering, AssocaitionRuleLearning, Deep Learning and Natural Language Processing Techniques

Data sampling library

These are all of my machine learning codes.You can find every code about machine learning.

Predicts gender of an author based on syntactic constructions of their tweets

Artificial intelligence model that detects intrusions in a network by analyzing TCP / IP packets by machine learning algorithms

My very first hands on experiment with CV

Machine Learning Task implemented in PySpark to parallelise K-Fold Cross Validation

Data sampling library

This is an algorithm for evenly partitioning.