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.
neurodsp is a collection of approaches for applying digital signal processing to neural time series, including algorithms that have been proposed for the analysis of neural time series. It also inclu
metric-learn: Metric Learning in Python metric-learn contains efficient Python implementations of several popular supervised and weakly-supervised met
The Emergence of Individuality
📚 Descrição Neste curso da Dell aprofundamos nossos conhecimentos em Machine Learning. 🖥️ Aulas (Em curso) 1.1 - Python aplicado a Data Science 1.2
Banpei Banpei is a Python package of the anomaly detection. Anomaly detection is a technique used to identify unusual patterns that do not conform to
fMRIprep Pipeline To Machine Learning(Demo) 所有配置均在config.py文件下定义 前置环境(lilab) 各个节点均安装docker，并有fmripre的镜像 可以使用conda中的base环境（相应的第三份包之后更新） 1. fmriprep scr
Efficient ML solutions for long-tailed demands.
🎛 lazycluster Distributed machine learning made simple. Use your preferred distributed ML framework like a lazy engineer. Getting Started • Highlight
Python Machine Learning Jupyter Notebooks (ML website) Dr. Tirthajyoti Sarkar, Fremont, California (Please feel free to connect on LinkedIn here) Also
Diabetes Prediction Using Decision Tree Introduction Decision tree is the most powerful and popular tool for classification and prediction. A Decision
The Machine Learning package simply contains sample datasets at present. It has some classification algorithms such as QSVM and VQC (Variational Quantum Classifier), where this data can be used for e
To design and implement the Identification of Iris Flower species using machine learning using Python and the tool Scikit-Learn.
Python API for the Crunchdao machine learning tournament Interact with the Crunc
TensorFlow-Time-Series-Examples Additional examples for TensorFlow Time Series(TFTS). Read a Time Series with TFTS From a Numpy Array: See "test_input
Puesta en Producción de un modelo de aprendizaje automático con Flask y Heroku L
Typilus: Suggest Python Type Annotations A GitHub action that suggests type annotations for Python using machine learning. This action makes suggestio
pyts: a Python package for time series classification pyts is a Python package for time series classification. It aims to make time series classificat
Python Causal Impact Causal inference using Bayesian structural time-series models. This package aims at defining a python equivalent of the R CausalI
A simple end to end consumer lending decision engine powered by Google Cloud Platform (firebase hosting and cloudrun)
TimeSynth Multipurpose Library for Synthetic Time Series Please cite as: J. R. Maat, A. Malali, and P. Protopapas, “TimeSynth: A Multipurpose Library
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