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-mbti-myers-briggs-personality-type-dataset icon -mbti-myers-briggs-personality-type-dataset

The Myers Briggs Type Indicator (or MBTI for short) is a personality type system that divides everyone into 16 distinct personality types across 4 axis: Introversion (I) – Extroversion (E) Intuition (N) – Sensing (S) Thinking (T) – Feeling (F) Judging (J) – Perceiving (P) (More can be learned about what these mean here) So for example, someone who prefers introversion, intuition, thinking and perceiving would be labelled an INTP in the MBTI system, and there are lots of personality based components that would model or describe this person’s preferences or behaviour based on the label. It is one of, if not the, the most popular personality test in the world. It is used in businesses, online, for fun, for research and lots more. A simple google search reveals all of the different ways the test has been used over time. It’s safe to say that this test is still very relevant in the world in terms of its use. From scientific or psychological perspective it is based on the work done on cognitive functions by Carl Jung i.e. Jungian Typology. This was a model of 8 distinct functions, thought processes or ways of thinking that were suggested to be present in the mind. Later this work was transformed into several different personality systems to make it more accessible, the most popular of which is of course the MBTI. Recently, its use/validity has come into question because of unreliability in experiments surrounding it, among other reasons. But it is still clung to as being a very useful tool in a lot of areas, and the purpose of this dataset is to help see if any patterns can be detected in specific types and their style of writing, which overall explores the validity of the test in analysing, predicting or categorising behaviour. Content This dataset contains over 8600 rows of data, on each row is a person’s: Type (This persons 4 letter MBTI code/type) A section of each of the last 50 things they have posted (Each entry separated by "|||" (3 pipe characters)) Acknowledgements This data was collected through the PersonalityCafe forum, as it provides a large selection of people and their MBTI personality type, as well as what they have written. Inspiration Some basic uses could include: Use machine learning to evaluate the MBTIs validity and ability to predict language styles and behaviour online. Production of a machine learning algorithm that can attempt to determine a person’s personality type based on some text they have written.

1on1-questions icon 1on1-questions

Mega list of 1 on 1 meeting questions compiled from a variety to sources

1on1tracker icon 1on1tracker

One-on-one tracking app for managers and their direct reports written in React and Firebase built and designed for the mobile web.

amazon-jobs-scraper icon amazon-jobs-scraper

Creating a CSV file with the jobs available at a particular URL of the Amazon.jobs website.

cover-letter-generator icon cover-letter-generator

WIP -- Generates a cover letter (.pdf, .doc) based off posted job description to optimize for key word hits in ATS software.

cvscan icon cvscan

Your not so typical resume parser

igcontentgenerator icon igcontentgenerator

Automated content generation for Instagram account written in Python using PIL and Pandas.

jobbyboy icon jobbyboy

JobbyBoy is a custom resume generator for software engineers. Users can create custom skills, experiences, and technologies, then dynamically generate resumes based on a job description.

linkedin_text_generator icon linkedin_text_generator

Created a web scraper to pull data science job descriptions off of LinkedIn. This is then cleaned and organized into a pandas dataframe. Then the job description text is embedded and a neural net is built to generate new data science job descriptions.

marked icon marked

A markdown parser and compiler. Built for speed.

mbti-net icon mbti-net

A Neural Network Approach To Classifying Myers Brigg Personality Type Through Writing

police-scanner-analysis icon police-scanner-analysis

A real-time lambda architecture pipeline that runs sentiment analysis on streaming audio data. Deployed to EMR cluster and configured to ingest police scanner radio.

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