This repository contains my implementation of the algorithms described in the book "Data Science From Scratch" by Joel Grus. I used Python 3.7 to code these algorithms.
| S.No. | File name | Description |
|---|---|---|
| 1 | classes_set.py | Illustrates how to create classes in Python |
| 2 | visualization.py | Illustartes how to create bar, scatter and line plots. |
| 3 | vector_operations.py | Illustrates how to create and manipulate vectors in Python |
| 4 | matrix_operations.py | Illustrates how to create and manipulate matrices in Python |
| 5 | statistics.py | Computes basic statstics including mean, variance, covariance, correlation etc. from the data. |
| 6 | probability.py | Demonstrates basic porbability operations in Python. |
| 7 | hypothesis_testing.py | Performs basic hypothesis testing in Python. |
| 8 | gardient_descent.py | Implementation of batch, mninbatch and stochastic gradient descent algorithm (IPython Notebook). |
| 9 | working_with_data.py | Demonstrates how to do data correlation, rescaling and dimensionality reduction - PCA algorithm implemented from scratch.(IPython Notebook). |
| 10 | machine_learning.py | Computes model assessment metrics like accuracy, precision, recall and F1-score. (IPython Notebook). |
| 11 | k_nearest_neighbors.py | Implemention of k-nearest neighbors algorithm from scratch in Python. (IPython Notebook). |
| 12 | naive_bayes.py | Implemention of Naive Bayes algorithm from scratch in Python. (IPython Notebook). |
| 13 | linear_regression.py | Implemention of simple linear regression algorithm from scratch in Python. (IPython Notebook). |
| 14 | multiple_regression.py | Implemention of simple linear regression algorithm from scratch in Python. (IPython Notebook). |
| 15 | logistic_regression.py | Implemention of simple logistic regression algorithm from scratch in Python. (IPython Notebook). |
| 16 | decision_trees.py | Implemention of decision trees from scratch in Python. (IPython Notebook). |
| 17 | neural_networks.py | Implementation of feed-forward neural networks and backpropagation algorithm from scratch in Python. (IPython Notebook). |
| 18 | deep_learning.py | Implementation of deep neural networks with various loss fucntions and optimization techniques including network regulation using dropout from scratch in Python. (IPython Notebook). |
| 19 | clustering.py | Implementation of k-means and bottom-up hierarchical clustering from scratch in Python. (IPython Notebook). |
| 20 | nlp.py | Implementation of popular natural language processing algorithms including bigrams, trigrams, topic modeling, word vectors and recurrent neural networks from scratch in Python (IPython Notebook). |
| 21 | network_analysis.py | Demonstrates how to do simple network analysis in Python (IPython Notebook). |
| 22 | recommender_systems.py | Implementation of user and item based collaborative filtering, and a matrix factorization algorithm in Python.(IPython Notebook). |
| 23 | databases_sql.py | This file contains an impelementation of basic SQL operations in Python.(IPython Notebook). |
| 24 | MapReduce.py | An impelementation of mapper and reducer functions with a few examples in Python.(IPython Notebook). |