Implementations of essential machine learning algorithms from scratch
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Updated
May 28, 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.
Implementations of essential machine learning algorithms from scratch
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 implementations of Boosting method, aimed at improving predictive performance by combining multiple models. by using titanic database."
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
A concept on how Machine Learning (ML) can be integrated on Web apps
Machine learning multi classification model
Return over investment machine learning regression model