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.
Cross validation phases are given as comment with their results. They can be uncommented and tested again.
Hivemind: decentralized deep learning in PyTorch Hivemind is a PyTorch library to train large neural networks across the Internet. Its intended usage
=================================================== Nitime: timeseries analysis for neuroscience data ===============================================
The unified machine learning framework, enabling framework-agnostic functions, layers and libraries. Contents Overview In a Nutshell Where Next? Overv
Regularized Greedy Forest Regularized Greedy Forest (RGF) is a tree ensemble machine learning method described in this paper. RGF can deliver better r
Relating-Social-Media-to-Stock-Movement-Public - We explore the application of Machine Learning for predicting the return of the stock by using the information of stock returns. A trading strategy ba
This project is made to help you scale from a basic Machine Learning project for research purposes to a production grade Machine Learning web service
AppleStore-classification-with-Machine-learning-Algo- using Machine Learning Algorithm to classification AppleStore application. the first step : 1: p
GRAIL A Python implementation of GRAIL, a generic framework to learn compact time series representations. Requirements Python 3.6+ numpy scipy tslearn
OptaPy is an AI constraint solver for Python to optimize the Vehicle Routing Problem, Employee Rostering, Maintenance Scheduling, Task Assignment, School Timetabling, Cloud Optimization, Conference S
Predico Disease Prediction system based on symptoms provided by patient- using Python-Django & Machine Learning
TimeSynth Multipurpose Library for Synthetic Time Series Please cite as: J. R. Maat, A. Malali, and P. Protopapas, “TimeSynth: A Multipurpose Library
Short PhD seminar on Machine Learning Security (Adversarial Machine Learning)
Dynet A concept I came up which ditches the idea of "layers" in a neural network. Install Copy Dynet.py to your project. Run the example Install matpl
Intro-to-Data-Science Conducted ANOVA and Logistic regression analysis. Project ANOVA The main aim of this project is to perform One-Way ANOVA analysi
A machine learning project that predicted binding sites of AP1 transcription factor, using ChIP-Seq data and local DNA shape information.
Falken provides developers with a service that allows them to train AI that can play their games. Unlike traditional RL frameworks that learn through rewards or batches of offline training, Falken is
FEATURE ENGINEERING Business Problem: A data preprocessing and feature engineering script for a machine learning pipeline needs to be prepared. It is
Databricks Certification Spark Databricks Certified Associate Spark Developer preparation toolkit to setup single node Standalone Spark Cluster along
Apache SINGA Distributed deep learning system http://singa.apache.org Quick Start Installation Examples Issues JIRA tickets Code Analysis: Mailing Lis
InfiniteBoost Code for a paper InfiniteBoost: building infinite ensembles with gradient descent (arXiv:1706.01109). A. Rogozhnikov, T. Likhomanenko De
1.3k Jan 08, 2023
212 Dec 09, 2022
8.2k Dec 31, 2022
363 Dec 14, 2022
15 Oct 29, 2022
10 Apr 04, 2022
2 May 02, 2022
3 Nov 24, 2021
208 Dec 27, 2022
1 Jan 06, 2022
278 Dec 26, 2022
141 Dec 27, 2022
4 Dec 05, 2021
1 Feb 06, 2022
1 Jan 21, 2022
223 Jan 03, 2023
7 Dec 18, 2021
19 Dec 13, 2022
2.7k Jan 05, 2023
183 Jan 03, 2023