aitools 0.1.3

Artificial Intelligence Tool Kit Mark Two.

AITools

Artificial Intelligence Tool Kit Mark Two.

• Free software: Apache Software License 2.0

• Documentation: https://aitools.readthedocs.io.

Features

• N-GRAM

  • Predict the next word of the sentence that further can be use for predicting the entire sentence.

  • Generation of text like a paragraph/article on Health or environment or any other topic (given relevant data).

  • Generation of the next GOT books!!!.

  • Next Phase - Use of bayesian statistics and more nice probability models for getting the best results.

Look For: Demo file n_gram.py

• K-MEANS

  • Creates clusters and classify new nodes into those clusters.

  • Efficient and easy to implement.

  • Next Phase - Multiple algorithms implementation.

Look For: Demo file k_means.py and k_means_color_cluster.py

• Logistic Regression

  • From probability of event happening or not to the next Data point, it is a very versatile algorithm.

  • Simple Implementation and Training routines.

  • Uses Gradient Descent and Sigmoid Function.

  • Next Phase - Improvements in Gradient Descent is still in progress.

Look For: Demo file logistic_regression.py

• Naive Bayes

  • Algorithm based on Bayesian statistics, which is capable of creating classifications like an intent classifier or sentiment analysis engine(A true complex one not the Pathetic Twitter thing).

  • Created using little bit of probability and bayesian statistics with a hint of programming and with a lot of love.

  • Next Phase - Flexibility and more control on different algorithm.

Look For: Demo file naive_bayes.py

• Decision Tree

  • Algorithm based on Gini logic and info gain for prediction.

  • Trees can be very use full but may lead to aver fitting easily Be Cautious.

  • Next Phase - Flexibility and more control on different algorithm.

Look For: Demo file decision_tree.py

• Pre Processing

  • Utils for Pre Processing Data.

  • Next Phase - More Cool Functions.

Look For: Demo file pre_processing.py

• Others

  • In build Mathematics Util.

    • Vector Math, Probability, and some Statistic

    • Util will be upgraded as per the need.

  • Gradient Descent.

    • Entire Gradient Descent algorithm combined into one.

    • Usability Docs will be Provided Soon.

• Next Updates

  • Improving all algorithms and giving proper documentation on usage.

  • Providing more user control on algorithm selection and output handling.

  • Detailed Demo files.

  • Sudo codes and algorithm explanations.

  • Will be available to lower version( > 2.7).

Credits

This package was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template.

History

0.1.0 (2019-04-14)

• GitHub Setup.

• Travis CI Build Added.

• Documentation skeleton added on ReadTheDocs.

• First release on PyPI.

0.1.0 (2019-04-21)

• N-Gram algorithm version one completed.

• First level of documentation.

• N-Gram demo files added.

0.1.0 (2019-04-25)

• Gradient Descent Created.

• Word Stemmer Added(Still needs improvements and not been used through out the project).

0.1.0 (2019-04-28)

• Logistic Regression Added.

• Demo file added.

0.1.2 (2019-05-01)

• Naive Bayes Created.

0.1.2 (2019-05-01)

• Pre Processing Added.

0.1.2 (2019-05-01)

• First Level of Documentation Created.

0.1.2 (2019-05-27)

• Lost Track of most of the things.

• Finally We have following

  • K Means

  • Logistic Regression

  • N Gram

  • Naive Bayes

  • Pre Processing

  • SVM in progress.

0.1.3 (2019-06-24)

• Decision Tree Added(Gini and Impurity Method).

• Previous algorithm improvements are in progress.