Summary for MSE module Algorithms.

Zusammenfassung für das MSE Modul TSM_EmbHardw

Cross-validation, knn classif, knn régression, svm à noyau, Ridge à noyau

Regression algorithms to predict the median house prices in California districts

선물 지수와 주가의 상관 관계에 대한 연구와 분석

MSE: From Fourier To Wavelets

A simple Linear Regression project from scratch in Python 3.

In this Notebook, MSE of three models (LinearRegression, Polynomial, and 3-layer Neural Network using Keras) has calculated and compared

This project focuses on identifying the best hyperparameters for modeling and predicting trends in food sales using a Multi-Layer Perceptron (MLP) neural network. The objective is to optimize the MLP model to achieve high predictive accuracy, enabling businesses to make informed decisions regarding inventory management and sales strategies.

This project focuses on predicting the burned area of forest fires using Long Short-Term Memory (LSTM) neural networks. The LSTM model is trained on historical data to forecast the extent of forest fire damage based on various environmental and meteorological factors.

Mini-learn is a miniature version of tensor-flow which I made with ONLY NUMPY to play with perceptrons. You can use this project like you use tflearn. Go to https://github.com/Satyaki0924/boston-housing-with-minilearn to see it's usage.

Zusammenfassung für das MSE Modul FTP_AppStat

Implementing Neural Network on Irish data - evaluating accuracy, Mean Squared Error (MSE), Crossentropy and log-likelihood

MSE Module Computational Algebra and Numerical Analysis by Bernhard Zgraggen

Summary for MSE module Electrical Energy Systems

Calculating the mean squared error of each images after being processed

Implementation of a simple linear regression with single feature