overfitting

Transformer-Based-Amharic-to-English-Machine-Translation-with-Character-Embedding-and-Combined-Regul

Machine-Learning

Códigos e enunciados utilizados no curso de Aprendizado de Máquina feito em 2020.

regularization-neural-networks

Simple Demo to show how L2 Regularization avoids overfitting in Deep Learning/Neural Networks

python_bootcamp

42AI Bootcamps - Python & Machine Learning

Machine-learning

Python version of Andrew Ng's Machine Learning Course.

Algo-Strategy-Backtesting

Algorithmic Strategy Backtesting

regression-models

A series of documented Jupyter notebooks implementing polynomial regression models and model performance analysis

Classification-Optimization-technique

Fraud detection over twitter feed data

Speech-Emotion-Recognition-

Predicting various emotion in human speech signal by detecting different speech components affected by human emotion.

Machine-Learning-Specialization

Machine Learning: Regression and Classification. Andrew presents a course in introduction to machine learning, with practice in regression and classification for the first and second course, and the third course focuses on recommender systems and reinforcement learning.

Daily_Work_of_Data_Science

資料科學的日常研究議題

Decision_Tree

Implementation of Decision Tree and Random Forest algorithms, with various hyperparameters, developed from scratch and using scikit-learn for comparison and analysis.

Pet-Image-Classification

Classification between pet images using different approaches on famous cats vs dogs dataset available on kaggle.

EvaluationMetric

Evaluating classifier using Python focus on evaluation metrics and hyperparameter turning

project-bankruptcy-prediction

Binary Classification with XGBoost to predict the future bankruptcy status of Polish companies. Supervised Machine Learning (Capstone Project).

global-optimization

Unknown function approximation, given input-output measurements, using Genetic Algorithm

dropout-walkthrough

A repository to show how Dropout in Keras can Prevent Overfitting

Machine-Learning

:construction: ML algorithms, employing different approaches

NeuralNetwork

An implementation of neural network with regularization

Noise-Regularization-Method-Neural-Network

Adding noise as regularization method to reduce overffiting in neural networks

deep_learning_with_python

My notebooks on the book "Deep Learning with Python" by Francois Chollet (2018)

XinshaoAmosWang.github.io

Xinshao Wang, Ex-Postdoc and Ex-Visit Scholar@University of Oxford, Ex-Senior Researcher@ZenithAI

ML-Logistic-Regression

Logistic Regression algorithm to classify two classes of 2-D data samples using 1) 2-D feature vector & 2) its mapping to a higher dimensional feature space.

OverFitting

Analyse OverFitting of data

us-state-under-over-fitting

A visual example of the concepts of under and overfitting in supervised machine learning using U.S. state border data.

Machine-Learning-Utils

This repository contains the Python code and solutions for machine learning, including supervised and unsupervised learning, regularization, cross-validation, PCA, and support vector machines (SVM).

PhiMonitor

Python library for monitoring machine learning models, detecting data drift and overfitting to ensure robust and reliable performance.

Python-Project-Analysis-for-ClimateWins

This project analyzes historical weather data to identify patterns and predict future weather conditions, focusing on extreme events and temperature trends across Europe.

Time_series_analysis

An attempt to master Time series analysis

Guide-to-Regularization

Regularization is a crucial technique in machine learning that helps to prevent overfitting. Overfitting occurs when a model becomes too complex and learns the training data so well that it fails to generalize to new, unseen data.

HighDimensionalData

Code used to generate results from Chapter 18 of The Elements of Statistical Learning

Cats_vs_Dogs_Classification

This project focuses on classifying images of cats and dogs using Convolutional Neural Networks (CNNs) with PyTorch. The dataset used for this project is from Kaggle's "Dogs vs Cats Redux" competition.

data-augmentation-cnn

This repository explores how data augmentation helps mitigate overfitting in CNNs with limited training data.

ReducingOverfitting

Reducing overfitting in perdiction in decision trees

Machine_Learning-Gradient_descent_with_Logistic_Regression

Content: Classification, Sigmoid function, Decision Boundary, Cost function, Gradient descent, Overfitting, Regularisation