Machine Learning Algorithms ( Desion Tree, XG Boost, Random Forest )
Overview
Magenta: Music and Art Generation with Machine Intelligence
Magenta is a research project exploring the role of machine learning in the process of creating art and music. Primarily this involves developing new
Implementation of deep learning models for time series in PyTorch.
List of Implementations: Currently, the reimplementation of the DeepAR paper(DeepAR: Probabilistic Forecasting with Autoregressive Recurrent Networks
Python module for machine learning time series:
seglearn Seglearn is a python package for machine learning time series or sequences. It provides an integrated pipeline for segmentation, feature extr
A logistic regression model for health insurance purchasing prediction
Logistic_Regression_Model A logistic regression model for health insurance purchasing prediction This code is using these packages, so please make sur
inding a method to objectively quantify skill versus chance in games, using reinforcement learning
Skill-vs-chance-games-analysis - Finding a method to objectively quantify skill versus chance in games, using reinforcement learning
Simple, light-weight config handling through python data classes with to/from JSON serialization/deserialization.
Simple but maybe too simple config management through python data classes. We use it for machine learning.
A toolbox to iNNvestigate neural networks' predictions!
iNNvestigate neural networks! Table of contents Introduction Installation Usage and Examples More documentation Contributing Releases Introduction In
Pandas Machine Learning and Quant Finance Library Collection
Pandas Machine Learning and Quant Finance Library Collection
This repository has datasets containing information of Uber pickups in NYC from April 2014 to September 2014 and January to June 2015. data Analysis , virtualization and some insights are gathered here
uber-pickups-analysis Data Source: https://www.kaggle.com/fivethirtyeight/uber-pickups-in-new-york-city Information about data set The dataset contain
A library to generate synthetic time series data by easy-to-use factors and generator
timeseries-generator This repository consists of a python packages that generates synthetic time series dataset in a generic way (under /timeseries_ge
Automatic extraction of relevant features from time series:
tsfresh This repository contains the TSFRESH python package. The abbreviation stands for "Time Series Feature extraction based on scalable hypothesis
A collection of interactive machine-learning experiments: 🏋️models training + 🎨models demo
🤖 Interactive Machine Learning experiments: 🏋️models training + 🎨models demo
Gaussian Process Optimization using GPy
End of maintenance for GPyOpt Dear GPyOpt community! We would like to acknowledge the obvious. The core team of GPyOpt has moved on, and over the past
ML-powered Loan-Marketer Customer Filtering Engine
In Loan-Marketing business employees are required to call the user's to buy loans of several fields and in several magnitudes. If employees are calling everybody in the network it is also very length
Solve automatic numerical differentiation problems in one or more variables.
numdifftools The numdifftools library is a suite of tools written in _Python to solve automatic numerical differentiation problems in one or more vari
Climin is a Python package for optimization, heavily biased to machine learning scenarios
climin climin is a Python package for optimization, heavily biased to machine learning scenarios distributed under the BSD 3-clause license. It works
MiniTorch - a diy teaching library for machine learning engineers
This repo is the full student code for minitorch. It is designed as a single repo that can be completed part by part following the guide book. It uses
A chain of stores, 10 different stores and 50 different requests a 3-month demand forecast for its product.
Demand-Forecasting Business Problem A chain of stores, 10 different stores and 50 different requests a 3-month demand forecast for its product.
fastFM: A Library for Factorization Machines
Citing fastFM The library fastFM is an academic project. The time and resources spent developing fastFM are therefore justified by the number of citat
Machine learning algorithms implementation
Machine learning algorithms implementation This repository consisits of implementation of various machine learning algorithms. The algorithms implemen