Random Forest Classification for Neural Subtypes

Overview

Random Forest Classification for Neural Subtypes

This notebook is focussed on stepping through a Random Forest classifier for neural subtypes extracted from extracellular recordings from human brain organoids. We will step through multi-demsionality reduction, clustering, waveform plotting and confusion matrices. Notably, this is a simple data analysis notebook for the purpose of a Medium & Kaggle contribution.

Waveform plotting

Multi-dimensionality reduction

Clustering

Data breakdown

Random forest

Owner
Michael Zabolocki
PhD candidate in Human Neurophysiology & Genetics.
Michael Zabolocki
The MLOps is the process of continuous integration and continuous delivery of Machine Learning artifacts as a software product, keeping it inside a loop of Design, Model Development and Operations.

MLOps The MLOps is the process of continuous integration and continuous delivery of Machine Learning artifacts as a software product, keeping it insid

Maykon Schots 25 Nov 27, 2022
A data preprocessing and feature engineering script for a machine learning pipeline is prepared.

FEATURE ENGINEERING Business Problem: A data preprocessing and feature engineering script for a machine learning pipeline needs to be prepared. It is

Pinar Oner 7 Dec 18, 2021
Simple and flexible ML workflow engine.

This is a simple and flexible ML workflow engine. It helps to orchestrate events across a set of microservices and create executable flow to handle requests. Engine is designed to be configurable wit

Katana ML 295 Jan 06, 2023
Cool Python features for machine learning that I used to be too afraid to use. Will be updated as I have more time / learn more.

python-is-cool A gentle guide to the Python features that I didn't know existed or was too afraid to use. This will be updated as I learn more and bec

Chip Huyen 3.3k Jan 05, 2023
healthy and lesion models for learning based on the joint estimation of stochasticity and volatility

health-lesion-stovol healthy and lesion models for learning based on the joint estimation of stochasticity and volatility Reference please cite this p

5 Nov 01, 2022
Machine Learning Techniques using python.

šŸ‘‹ Hi, I’m Fahad from TEXAS TECH. šŸ‘€ I’m interested in Optimization / Machine Learning/ Statistics 🌱 I’m currently learning Machine Learning and Stat

FAHAD MOSTAFA 1 Jan 19, 2022
Mixing up the Invariant Information clustering architecture, with self supervised concepts from SimCLR and MoCo approaches

Self Supervised clusterer Combined IIC, and Moco architectures, with some SimCLR notions, to get state of the art unsupervised clustering while retain

Bendidi Ihab 9 Feb 13, 2022
Regularization and Feature Selection in Least Squares Temporal Difference Learning

Regularization and Feature Selection in Least Squares Temporal Difference Learning Description This is Python implementations of Least Angle Regressio

Mina Parham 0 Jan 18, 2022
LibTraffic is a unified, flexible and comprehensive traffic prediction library based on PyTorch

LibTraffic is a unified, flexible and comprehensive traffic prediction library, which provides researchers with a credibly experimental tool and a convenient development framework. Our library is imp

432 Jan 05, 2023
Backtesting an algorithmic trading strategy using Machine Learning and Sentiment Analysis.

Trading Tesla with Machine Learning and Sentiment Analysis An interactive program to train a Random Forest Classifier to predict Tesla daily prices us

Renato Votto 31 Nov 17, 2022
Machine learning algorithms implementation

Machine learning algorithms implementation This repository consisits of implementation of various machine learning algorithms. The algorithms implemen

Karun Dawadi 1 Jan 03, 2022
Case studies with Bayesian methods

Case studies with Bayesian methods

Baze Petrushev 8 Nov 26, 2022
A Python library for detecting patterns and anomalies in massive datasets using the Matrix Profile

matrixprofile-ts matrixprofile-ts is a Python 2 and 3 library for evaluating time series data using the Matrix Profile algorithms developed by the Keo

Target 696 Dec 26, 2022
Uplift modeling and causal inference with machine learning algorithms

Disclaimer This project is stable and being incubated for long-term support. It may contain new experimental code, for which APIs are subject to chang

Uber Open Source 3.7k Jan 07, 2023
Open MLOps - A Production-focused Open-Source Machine Learning Framework

Open MLOps - A Production-focused Open-Source Machine Learning Framework Open MLOps is a set of open-source tools carefully chosen to ease user experi

Data Revenue 590 Dec 28, 2022
LiuAlgoTrader is a scalable, multi-process ML-ready framework for effective algorithmic trading

LiuAlgoTrader is a scalable, multi-process ML-ready framework for effective algorithmic trading. The framework simplify development, testing, deployment, analysis and training algo trading strategies

Amichay Oren 458 Dec 24, 2022
CorrProxies - Optimizing Machine Learning Inference Queries with Correlative Proxy Models

CorrProxies - Optimizing Machine Learning Inference Queries with Correlative Proxy Models

ZhihuiYangCS 8 Jun 07, 2022
A project based example of Data pipelines, ML workflow management, API endpoints and Monitoring.

MLOps template with examples for Data pipelines, ML workflow management, API development and Monitoring.

Utsav 33 Dec 03, 2022
Flask app to predict daily radiation from the time series of Solcast from Islamabad, Pakistan

Solar-radiation-ISB-MLOps - Flask app to predict daily radiation from the time series of Solcast from Islamabad, Pakistan.

Abid Ali Awan 1 Dec 31, 2021
Covid-polygraph - a set of Machine Learning-driven fact-checking tools

Covid-polygraph, a set of Machine Learning-driven fact-checking tools that aim to address the issue of misleading information related to COVID-19.

1 Apr 22, 2022