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Machine learning algorithms implementation from scratch using python

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ML Problem Solving

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Machine learning algorithms implementation from scratch using python

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Table of Content

1. Bag of Words (BOW):

Coverts a collection of documents to a matrix, with each document being a row and each word(token) being the column, and the corresponding (row,column) values being the frequency of occurrance of each word or token in that document.
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2. Mini-Batch Gradient Descent Implementation for Linear Regression:

An optimization algorithm used for computing the model parameters for algorithms like linear regression, logistic regression, neural networks.
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3. Perceptron Algorithm:

Binary classification machine learning algorithm that is the simplest type of neural network model.
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4. Perceptron Algorithm as Logical Operations:

Use the perceptroin algorithms as AND,OR and Not logical operator.
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5. Naive Bayes:

Bayes Theorem is one of the earliest probabilistic inference algorithms. It was developed by Reverend Bayes (which he used to try and infer the existence of God.

6. Metrics:

Classifiction metrics implementation:

  • Accuracy
  • Precision
  • Recall
  • F1 score
  • AUC and ROC curve

Regression metrics implementation:

  • R-squared
  • Mean absolute error
  • Mean square error