Code and exercises of the Machine Learning Crash Course
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Updated
Jun 28, 2018 - Python
Code and exercises of the Machine Learning Crash Course
The "Hello World" of machine learning with the iris classification dataset, coded in Python
Colorize black & white images, using machine learning in Python
Bootcamp python organised by 42's association 42AI
《机器学习实战》Python3实现
Creating a logistic regression algorithm without using a library and making cancer classification with this algorithm model (Kaggle Explained)
This Python code represents a machine learning project that builds a simple linear regression model using experience and salary data. It plots the data, constructs the regression model, and visualizes the results.
Machine Learning library using what I learned from CS4780, using NumPy only. It supports Bayesian inference, kernelization, ensembles, deep learning, convolutional NN, and Transformers.
ganesh kavhar pygames development..
Deep learning basic blocks
Implementations of Machine Learning algorithms with Python and Numpy.
Stock Price Prediction Using Quandl in 5 Steps
contains the content related to ML
Making cancer classification with knn module (Kaggle Expression)
An example showing various TensorFlow & Machine Learning concepts.
K means clustering implementation on the wine quality dataset
Machine Learning Software that predicts planets based on their distance from the sun, number of satellites and various properties
Welcome to the Machine Learning Tutorials repository! This repository contains tutorials and code examples for various machine learning algorithms implemented in Python.
Implementation of Andrew Ng's Machine Learning Tutorial
PCA applied on images and Naive Bayes Classifier to classify them. Validation, cross validation and grid search with multi class SVM
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