README.md

Job classifier

Description

This is an example of text classification on job description dataset, using different classifiers with tuning techniques.

For solving this problem we follow the next steps:

• Exploratory data analysis
• Data preprocessing
• Modeling
• Show job position based on description

The classifier is built on dataset, which contains > 70k job descriptions belong to 30 job positions.

Example contains training 4 different classifiers with comparing results on validation dataset:

Classifier	Accuracy
Naive Bayes classifier	0.87
LogisticRegression	0.94
DecisionTreeClassifier	0.93
LinearSVC classifier	0.95

Example
Input text (job description):

Our client is a leading innovator in manufacturing thousands of products that affect the lives of millions of people every day; and a strategic player in the Home Health, Personal Care, Electronics, Industrial and Transportation Markets. Specifics:

• Prepare support for and record required journal entries related to general ledger accounts
• Prepare monthly account reconciliations
• Support and actively participate in department initiatives
• Assist with Ad-hoc analysis and projects

Output (job position):

Staff Accountant

Installation

With Kaggle API download dataset:

kaggle datasets download -d bman93/dataset

Dependencies:

pip install -r requirements.txt

Optional:

python -m spacy download en_core_web_sm