Machine Learning Algorithms ( Desion Tree, XG Boost, Random Forest )
Overview
Convoys is a simple library that fits a few statistical model useful for modeling time-lagged conversions.
Convoys is a simple library that fits a few statistical model useful for modeling time-lagged conversions. There is a lot more info if you head over to the documentation. You can also take a look at
Programming assignments and quizzes from all courses within the Machine Learning Engineering for Production (MLOps) specialization offered by deeplearning.ai
Machine Learning Engineering for Production (MLOps) Specialization on Coursera (offered by deeplearning.ai) Programming assignments from all courses i
A library of sklearn compatible categorical variable encoders
Categorical Encoding Methods A set of scikit-learn-style transformers for encoding categorical variables into numeric by means of different techniques
🚪✊Knock Knock: Get notified when your training ends with only two additional lines of code
Knock Knock A small library to get a notification when your training is complete or when it crashes during the process with two additional lines of co
XGBoost + Optuna
AutoXGB XGBoost + Optuna: no brainer auto train xgboost directly from CSV files auto tune xgboost using optuna auto serve best xgboot model using fast
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
Multiple Linear Regression using the LinearRegression class from sklearn.linear_model library
Multiple-Linear-Regression-master - A python program to implement Multiple Linear Regression using the LinearRegression class from sklearn.linear model library
This repo includes some graph-based CTR prediction models and other representative baselines.
Graph-based CTR prediction This is a repository designed for graph-based CTR prediction methods, it includes our graph-based CTR prediction methods: F
Price forecasting of SGB and IRFC Bonds and comparing there returns
Project_Bonds Project Title : Price forecasting of SGB and IRFC Bonds and comparing there returns. Introduction of the Project The 2008-09 global fina
A Python implementation of GRAIL, a generic framework to learn compact time series representations.
GRAIL A Python implementation of GRAIL, a generic framework to learn compact time series representations. Requirements Python 3.6+ numpy scipy tslearn
Pandas-method-chaining is a plugin for flake8 that provides method chaining linting for pandas code
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This repo implements a Topological SLAM: Deep Visual Odometry with Long Term Place Recognition (Loop Closure Detection)
This repo implements a topological SLAM system. Deep Visual Odometry (DF-VO) and Visual Place Recognition are combined to form the topological SLAM system.
Falken provides developers with a service that allows them to train AI that can play their games
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
Home repository for the Regularized Greedy Forest (RGF) library. It includes original implementation from the paper and multithreaded one written in C++, along with various language-specific wrappers.
Regularized Greedy Forest Regularized Greedy Forest (RGF) is a tree ensemble machine learning method described in this paper. RGF can deliver better r
A repository of PyBullet utility functions for robotic motion planning, manipulation planning, and task and motion planning
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Hierarchical Time Series Forecasting using Prophet
htsprophet Hierarchical Time Series Forecasting using Prophet Credit to Rob J. Hyndman and research partners as much of the code was developed with th
Bayesian optimization based on Gaussian processes (BO-GP) for CFD simulations.
BO-GP Bayesian optimization based on Gaussian processes (BO-GP) for CFD simulations. The BO-GP codes are developed using GPy and GPyOpt. The optimizer
(3D): LeGO-LOAM, LIO-SAM, and LVI-SAM installation and application
SLAM-application: installation and test (3D): LeGO-LOAM, LIO-SAM, and LVI-SAM Tested on Quadruped robot in Gazebo â—Ź Results: video, video2 Requirement
Module for statistical learning, with a particular emphasis on time-dependent modelling
Operating system Build Status Linux/Mac Windows tick tick is a Python 3 module for statistical learning, with a particular emphasis on time-dependent
A toolbox to iNNvestigate neural networks' predictions!
iNNvestigate neural networks! Table of contents Introduction Installation Usage and Examples More documentation Contributing Releases Introduction In