This project has Classification and Clustering done Via kNN and K-Means respectfully. It later tests its efficiency via F1/accuracy/recall/precision for kNN and Davies-Bouldin Index for Clustering. The Data is also visually represented.
For Additional Information please refer to the Documentation.
MLProject_01 This project impelemented for midterm of the Machine Learning #Zoomcamp #Alexey Grigorev Context Dataset English question data set file F
HH-VAEM This repository contains the official Pytorch implementation of the Hierarchical Hamiltonian VAE for Mixed-type Data (HH-VAEM) model and the s
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
Kaggle-Comp.-Data-Mining Kaggle Competition using 15 numerical predictors to predict a continuous outcome as part of a final project for a stats data
Predict the output which should give a fair idea about the chances of admission for a student for a particular university.
Robotics Toolbox for Python A Python implementation of the Robotics Toolbox for MATLAB® GitHub repository Documentation Wiki (examples and details) Sy
Horovod Horovod is a distributed deep learning training framework for TensorFlow, Keras, PyTorch, and Apache MXNet. The goal of Horovod is to make dis
Python-ELM v0.3 --- ARCHIVED March 2021 --- This is an implementation of the Extreme Learning Machine [1][2] in Python, based on scikit-learn. From
List of Implementations: Currently, the reimplementation of the DeepAR paper(DeepAR: Probabilistic Forecasting with Autoregressive Recurrent Networks
A repository for collating all the resources such as articles, blogs, papers, and books related to Bayesian Statistics.
High performance Python GLMs with all the features!
Automated machine learning: Review of the state-of-the-art and opportunities for healthcare
The aim of the mini project is predict whether or not a passenger survived based on attributes such as their age, sex, passenger class, where they embarked and more.
MBTR is a python package for multivariate boosted tree regressors trained in parameter space.
Auto_TS: Auto_TimeSeries Automatically build multiple Time Series models using a Single Line of Code. Now updated with Dask. Auto_timeseries is a comp
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 library was developed in order to facilitate rapid prototyping in Python of predictive machine-learning models using longitudinal medical data from an OMOP CDM-standard database.
Merlion is a Python library for time series intelligence. It provides an end-to-end machine learning framework that includes loading and transforming data, building and training models, post-processi
formulae formulae is a Python library that implements Wilkinson's formulas for mixed-effects models. The main difference with other implementations li
Python Research Framework
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