"This repository contains implementations of Boosting method, aimed at improving predictive performance by combining multiple models. by using titanic database."
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Updated
Jun 1, 2024 - Jupyter Notebook
Machine learning is the practice of teaching a computer to learn. The concept uses pattern recognition, as well as other forms of predictive algorithms, to make judgments on incoming data. This field is closely related to artificial intelligence and computational statistics.
"This repository contains implementations of Boosting method, aimed at improving predictive performance by combining multiple models. by using titanic database."
Implementations of essential machine learning algorithms from scratch
Predict and prevent customer churn in the telecom industry with this project. Leverage advanced analytics and ML on a diverse dataset to build a robust classification model. Gain a deep understanding of customer behavior and identify key factors influencing churn. Clone the repository, explore insights, and enhance customer retention startegies.
Animation Tweening of 3D vertex data using a Feed-Forward Neural Network.
Machine learning basics and some instructive projects
A package that makes it trivial to create and evaluate machine learning pipeline architectures.
S.O.L.I.D. Principles for Machine Learning project.
This project explores user authentication on mobile devices through typing patterns, leveraging touch and motion data. Using machine learning models, particularly LSTM, the research demonstrates superior user classification accuracy compared to traditional RNN models, enhancing security against ATO attacks.
This is the repository of my study in Machine Learning Zoomcamp from DataTalksClub.
Implementing VADER, RoBERTa and TextCNN on a twitter dataset from Kaggle
"This repository contains implementations of Boosting method, popular techniques in Model Ensembles, aimed at improving predictive performance by combining multiple models. by using titanic database."
Analyse von Datensätzen mit verschiedenen ML-Algorithmen
The Fast Gradient Sign Method (FGSM) combines a white box approach with a misclassification goal. It tricks a neural network model into making wrong predictions. We use this technique to anonymize images.
Machine Learning library using what I learned from CS4780, using NumPy only. It supports Bayesian inference, kernelization, ensembles, deep learning, convolutional NN, and Transformers.
All my learnings from "Machine Learning with Python" course offered by "IBM" on Coursera are reflected here.
DU - DA Module 20 challenge
This repository contains a Python implementation of a Multiple Linear Regression model to predict a company's profit based on various expenditures and the company's state.
Provide exploratory data analysis of the water level dataset from the Three Gorges dam in China as well as develop a machine learning model to forecast upstream water levels.
Bachelor Thesis, Lennart Keidel - Machine Learning in Games of Imperfect Information