There are 1 repository under maching-learning topic.
Remove watermark automatically(Just can use for fixed position watermark till now). 自动水印消除算法的实现(目前只支持固定水印位置)。
Lecture Notes of Andrew Ng's Machine Learning Course
A python package that make tensorflow be able to read "Kaldi" scp/ark in an elegant way. May kaldi user happy to enter tensorflow world.
This repository is the implementation of several famous convolution neural network architecture with Keras. (Resnet v1, Resnet v2, Inception v1/GoogLeNet, Inception v2, Inception v3))
Convolutional Neural Network with Tensorflow and Object Detection with OpenCV for Kaggle Image Recognition challange
SigMat: A Classification Scheme for Gene Signature Matching
홉필드 네트워크 파이썬 Tkinter 구현 예제
Python practice/机器学习、OpenCV、数据结构Python实战练习
Breast Cancer Detection with Decision trees Algorithm And Bagging Normalizing
A face segmentation implementation of FarRL model (CVPR 2022) using Facer, a face analysis toolkit for modern research.
To explore the forming of 996 working mode by simulation game on wechat game platform.
We present a framework called TLF that builds a classifier for the target domain having only few labeled training records by transferring knowledge from the source domain having many labeled records. While existing methods often focus on one issue and leave the other one for the further work, TLF is capable of handling both issues simultaneously. In TLF, we alleviate feature discrepancy by identifying shared label distributions that act as the pivots to bridge the domains. We handle distribution divergence by simultaneously optimizing the structural risk functional, joint distributions between domains, and the manifold consistency underlying marginal distributions. Moreover, for the manifold consistency we exploit its intrinsic properties by identifying $k$ nearest neighbors of a record, where the value of k is determined automatically in TLF. Furthermore, since negative transfer is not desired, we consider only the source records that are belonging to the source pivots during the knowledge transfer. We evaluate TLF on seven publicly available natural datasets and compare the performance of TLF against the performance of eleven state-of-the-art techniques. We also evaluate the effectiveness of TLF in some challenging situations. Our experimental results, including statistical sign test and Nemenyi test analyses, indicate a clear superiority of the proposed framework over the state-of-the-art techniques.
:gem: :smoking: Consiste básicamente en realizar todas la anotaciones, asignaciones, laboratorios y demás códigos de la clase de Inteligencia Artificial.
this repo contains python scripts for training ML models and creating data visualizations pertaining to the UCI Wisconsin Breast Cancer Diagnosis dataset
Machine learning based classification on electrocardiogram (ECG) signals for Premature Ventricular Contraction (PVC) localization.
Project 2 for udacity nd230 course
SmartTrade is an Automatic Trading System with embedded machine learning algorithm, real-time portfolio visualization and automated execution
Work with historical air quality data and meteorological (weather) data of two cities, Beijing and London, and the goal is to forecast the air quality in future
Tool to generate SGE scripts based on an experiment config
A React.js based webapp demonstrating my project researching cellular automata and maching learning.
This is a Vodafone-Idea Internship ML project , it provides the rough flite fares on the basis of data entries like source , destination, no of stops , Flight Company . We have used kaggle dataset to train the model . The model works fine wirh 75%-80% efficiency.
Generates predictions for a list of cryptocurrencies. Made to be just a framework, performance can be improved with more ML models (LSTM, Reinforcement, SVR..) google-site-verification: google480abb259e214884.html
Using machine learning classification model to predict customer's churn
It can recognize Digits from 0 to 9. Used Local Binary Pattern (LBP) and Support Vector Machine (SVM).
Naive Bayes Algorithm Module for python. https://pypi.org/project/naivepy/
Trabalho tem foco em Redes Neurais Convolucionais e Redes Completamente Conectadas, onde serão aplicadas técnicas diferentes em cima do mesmo conjunto de dados com o objetivo de identificar se existe um gato em uma imagem.
Learning Machine Learning at Digital Talent Scholarship
evaluators for classification models