Statistical Methods for Machine Learning project - Muffins Vs Chihuahuas
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Updated
Jul 26, 2024 - Python
Statistical Methods for Machine Learning project - Muffins Vs Chihuahuas
This Project will perform linear regression on Automobiles MPG
Using machine learning, get the features and labels from the csv and perform cross fold validation and linear regression.
EasyTorch is a research-oriented pytorch prototyping framework with a straightforward learning curve. It is highly robust and contains almost everything needed to perform any state-of-the-art experiments.
An example of easytorch implementation on retinal vessel segmentation.
K-fold cross-validation implemented from scratch to aid in analysis of the MNIST dataset
e2e machine learning pipeline using a config based approach for classification problems. Supports grouping and grading classifiers in addition to online learning algorithms
This code includes reading the data file, data visualization, variable splitting, model building, prediction and different metrics calculation using knn.
This code includes reading the data file, data visualization, variable splitting, model building, prediction and different metrics calculation using knn.
Detecting Laryngeal Cancer from CT SCAN images using Improvised Deep Learning based Mask R-CNN Model
Pada project ini, akan dilakukan identifikasi nilai mata uang rupiah dengan menggabungkan metode ekstrasi ciri Local Binary Pattern dan metode klasifikasi Naïve Bayes. Serta untuk pengukuran akurasi identifikasi dilakukan dengan metode evaluasi K-Fold Cross Validation. Dataset yang digunakan berupa citra dengan rincian terdapat 120 citra yang te…
A thesis submitted in partial fulfilment of the award of the degree of MSc Computer Science (Software Engineering) from Staffordshire University
K fold cross validation for Tensorflow datasets
my machine learning practices for my third year in MFCI CS department
MLB Team Runs Allowed Prediction Project (Linear Regression)
POS Tagger
Implemented Linear Regression Algorithm from scratch to predict species in Iris data using k-fold cross validation
Personal Project 2: using machine learning algorithms to predict the existence of heart disease based on a numerical and categorical dataset.
Using the dataset compiled by Dean De Cock. Applying Feature Transformation, Feature Selection and K-fold Cross Validation
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