To-Be is a machine learning challenge on CodaLab Platform about Mortality Prediction. The challenge aims to adress the problems of medical imbalanced data classification.
I worked in a team of 3 to solve the challenge and we were able to achieve a score of 77% and rank in the top 3. We used a LGBMClassifier and a mix of two resampling techniques (RandomUnderSampler and BorderlineSMOTE).
timemachines Autonomous, univariate, k-step ahead time-series forecasting functions assigned Elo ratings You can: Use some of the functionality of a s
m2cgen (Model 2 Code Generator) - is a lightweight library which provides an easy way to transpile trained statistical models into a native code
scikit-multilearn scikit-multilearn is a Python module capable of performing multi-label learning tasks. It is built on-top of various scientific Pyth
Machine learning algorithms implementation This repository consisits of implementation of various machine learning algorithms. The algorithms implemen
To design and implement the Identification of Iris Flower species using machine learning using Python and the tool Scikit-Learn.
Tweets_Classification_Webpage The goal of this project is to be able to predict what rating customers on social media platforms would give to products
tslearn The machine learning toolkit for time series analysis in Python Section Description Installation Installing the dependencies and tslearn Getti
Reproducible Experiment Platform (REP) REP is ipython-based environment for conducting data-driven research in a consistent and reproducible way. Main
Machine Learning Engineering for Production (MLOps) Specialization on Coursera (offered by deeplearning.ai) Programming assignments from all courses i
Advanced-Machine-Learning This repository contains the code for the project Real
K Nearest Neighbors (KNN) algorithm In this Machine Learning world, there are various algorithms designed for classification problems such as Logistic
High Performance toolbox for Extreme Learning Machines. Extreme learning machines (ELM) are a particular kind of Artificial Neural Networks, which sol
Persimmon What is it? Persimmon is a visual dataflow language for creating sklearn pipelines. It represents functions as blocks, inputs and outputs ar
On Anytime Learning At Macroscale Learning from sequential data dumps (key) Requirements Python 3.7 Pytorch 1.9.0 Hydra 1.1.0 (pip install hydra-core
The unified machine learning framework, enabling framework-agnostic functions, layers and libraries. Contents Overview In a Nutshell Where Next? Overv
This machine learning model was developed for House Prices - Advanced Regression Techniques competition in Kaggle by using several machine learning models such as Random Forest, XGBoost and LightGBM.
Cohort-Intelligence-for-Mathematical-Functions About Cohort Intelligence : Cohort Intelligence ( CI ) is an optimization technique. It attempts to mod
pmdarima Pmdarima (originally pyramid-arima, for the anagram of 'py' + 'arima') is a statistical library designed to fill the void in Python's time se
AVOCADO HASS TIME SERIES VÀ PREDICT PRICE Trước khi vào Heroku muốn giao diện đẹp mọi người chuyển giúp mình theo hình bên dưới https://avocado-hass.h
This is an implementation of the proximal policy optimization algorithm for the C++ API of Pytorch. It uses a simple TestEnvironment to test the algorithm
343 Jan 04, 2023
2.3k Jan 03, 2023
802 Jan 01, 2023
1 Jan 03, 2022
1 Jan 11, 2022
1 Dec 30, 2021
2.3k Jan 05, 2023
663 Dec 31, 2022
173 Jan 05, 2023
1 Jan 30, 2022
1 Jan 08, 2022
174 Dec 07, 2022
194 Jan 04, 2023
8 Mar 29, 2022
8.2k Dec 31, 2022
1 Mar 02, 2022
2 Oct 25, 2021
1.3k Jan 06, 2023
3 Dec 18, 2021
59 Dec 09, 2022