An interactive approach to understanding Machine Learning using scikit-learn
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Updated
Jun 22, 2022 - Jupyter Notebook
An interactive approach to understanding Machine Learning using scikit-learn
Objective of the repository is to learn and build machine learning models using Pytorch. 30DaysofML Using Pytorch
Simple naive bayes implementation for weather prediction in python
A Python implementation of Naive Bayes from scratch.
All exercises for the course Elements of AI - Building AI
Gauss Naive Bayes in Python From Scratch.
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Examples of all Machine Learning Algorithm in Apache Spark
Unsupervised Learning (PCA) on Vehicle dataset
Stock Market Price Prediction: Used machine learning algorithms such as Linear Regression, Logistics Regression, Naive Bayes, K Nearest Neighbor, Support Vector Machine, Decision Tree, and Random Forest to identify which algorithm gives better results. Used Neural Networks such as Auto ARIMA, Prophet(Time-Series), and LSTM(Long Term-Short Memory…
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Functions and code snippets to help save the time!
This Telegram-Bot answers python questions by using stackoverflow subjects.
Email Spam Detection using Naive Bayes Algorithm (Udacity's Machine Learning Engineer Nanodegree )
Driver drowsiness is one of the causes of traffic accidents. According to the statistics; highway road crashes hold 11.09% of the total number of accidents. There are several reasons of drowsy driving such as: a lack of quality of sleep, may be overnight driving or having sleep disorders e.g. sleep apnea. However; all people should know that: Pe…
Naive Bayes with support for categorical and continuous data
An analysis of traffic accident data for the UK in 2014, using data from the UK Data Service. (Sourced from Kaggle with original data coming from UK Data Service. See wiki for complete citations.)
A Sentiment Analyzer for a set of Hotel Reviews using Naive Bayes Algorithm
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