Discover im-pek/Optimisation-Model_Augmentation Open Source project

Stars
1
Language
Created over 5 years ago
Updated over 5 years ago

im-pek

There are no reviews yet. Be the first to send feedback to the community and the maintainers!

An Optimisation + Model Augmentation project to derive best plant growth recipe. Includes concepts like linear regression, genetic algorithm, euclidean distance, uniform criterion, and cloud computing (integration with AWS DynamoDB).

LDA2Word_Topic_Modelling

LDA2Word is a novel topic modelling technique created in June 2019, by yours truly, Pek Yun Ning. It hybridises the older LDA and Word2Vec topic modelling algorithms to form this all-new algorithm.

Python

Logistic_Regression_-_Confusion_Matrix

An application of Logistic Regression and presentation of its accuracy and precision using Confusion Matrix. This was applied to a consumer complaints dataset.

Python

NLP-NER

Natural Language Processing and Named Entity Recognition to automatically get specific structured entities from unstructured texts / data input.

Python

LDA2Char_Topic_Modelling

LDA2Char is a novel topic modelling technique created in June 2019, by yours truly, Pek Yun Ning. It hybridises the older LDA and FastText topic modelling algorithms to form this all-new algorithm.

Python

Doc2X_Topic_Modelling

Doc2X is a novel topic modelling technique created in June 2019, by yours truly, Pek Yun Ning. It hybridises the older Doc2Vec and Corex topic modelling algorithms to form this all-new algorithm.

Python

autofit-excel-cell-widths-using-xlwings

Autofit excel cell widths (using xlwings). Xlwings is an extremely efficient, state-of-the-art python library to manage, edit, and manipulate excel files & data. Its documentation can be viewed at https://readthedocs.org/projects/xlwings/downloads/pdf/stable.

Python

im-pek/Optimisation-Model_Augmentation

im-pek

Reviews

Repository Details

More Repositories