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data-science-experiments's Introduction

Data Science Portfolio

1 Regular ML Algorithms

1.1 Decision tree

1.2 Random forest

1.3 Logistic regression

1.4 Support vector machine

1.5 Naive Bayes

1.6 k-NearestNeighbor

1.7 k-means

1.8 Adaboost

1.9 Markov

1.10 Least square regression

1.11 Principal Component Analysis

1.12 Singular Value Decomposition

2 Neural Network Algorithms

2.1 Convolutional Neural Network

2.2 Recurrent Neural Network

3 Dataset-based Explorations

3.1 Iris dataset

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