Author: Shengxuan Wang
From: Oregon State University
Building Machine Learning model from Scratch, without using any ML package. Only use data processing package, e.g. Pandas and Numpy, and a package I made: Popanda (see the detail here: https://github.com/shawn120/Popanda_Enhance_of_Pandas) Then using some data set to test them.
Models include Linear Regression, Logistic Regression, Perceptron, and Decision Tree.
Python API for the Crunchdao machine learning tournament Interact with the Crunc
Time-series-momentum Time-series momentum strategy. You can use the data_analysis.py file to find out the best trigger and window for a given asset an
05.income-prediction Predict the income for each percentile of the population (Python) - FRENCH Effectuez une prédiction de revenus Prérequis Pour ce
A python toolbox/library for data mining on partially-observed time series, supporting tasks of forecasting/imputation/classification/clustering on incomplete multivariate time series with missing va
Solar-radiation-ISB-MLOps - Flask app to predict daily radiation from the time series of Solcast from Islamabad, Pakistan.
This is a salary prediction website developed with the help of machine learning, this makes prediction of salary on basis of few parameters like interview score, experience test score.
A Python library for choreographing your machine learning research.
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
Petastorm Contents Petastorm Installation Generating a dataset Plain Python API Tensorflow API Pytorch API Spark Dataset Converter API Analyzing petas
Machine-Learning-for-Time-Series-with-Python Become proficient in deriving insights from time-series data and analyzing a model’s performance Links Am
Dragonfly is an open source python library for scalable Bayesian optimisation. Bayesian optimisation is used for optimising black-box functions whose
luminol Overview Luminol is a light weight python library for time series data analysis. The two major functionalities it supports are anomaly detecti
BioPy is a collection (in-progress) of biologically-inspired algorithms written in Python. Some of the algorithms included are mor
rpforest rpforest is a Python library for approximate nearest neighbours search: finding points in a high-dimensional space that are close to a given
pyGAM Generalized Additive Models in Python. Documentation Official pyGAM Documentation: Read the Docs Building interpretable models with Generalized
House Prices - Advanced Regression Techniques Predicting House Prices with Machine Learning This project is build to enhance my knowledge about machin
SLAM-application: installation and test (3D): LeGO-LOAM, LIO-SAM, and LVI-SAM Tested on Quadruped robot in Gazebo ● Results: video, video2 Requirement
📚 Descrição Neste curso da Dell aprofundamos nossos conhecimentos em Machine Learning. 🖥️ Aulas (Em curso) 1.1 - Python aplicado a Data Science 1.2
WAGMA-SGD is a decentralized asynchronous SGD based on wait-avoiding group model averaging. The synchronization is relaxed by making the collectives externally-triggerable, namely, a collective can b
Model Validation Toolkit is a collection of tools to assist with validating machine learning models prior to deploying them to production and monitoring them after deployment to production.
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