Python for Text Classification with Machine Learning in Python 3.6.
Start your environment by picking either pipenv (recommended) or virtualenv. Simple guides are below.
- Initialize pipenv (setup guide):
cd path/to/your/dev/folder
mkdir text-classify
cd text-classify
pipenv install --three
After installation of pipenv works, just activate it (same on all systems):
pipenv shell
- Project requirements
pip install numpy scipy scikit-learn jupyter
- Initialize virtualenv
cd path/to/your/dev/folder
mkdir text-classify
cd text-classify
virtualenv --python3 .
After installation of pipenv works, just activate it:
Mac / Linux
source bin/activate
Windows
.\Scripts\activate
- Project requirements
pip install numpy scipy scikit-learn jupyter
1 - Introduction no code
2 - Initialize Virtual Environment with Pipenv
3 - Sublime Text & Jupyter Notebooks no code
8 - One Hot Array Back to Text
9 - Bag of Words with External Data
10 - One Hot Array with External Data
11 - Training Data and Labels as Numpy Arrays
12 - Train and Predict with Sklearn SVM
14 - Reusable Sklearn Classifier
16 - Pickles no code
17 - Good Data In, Good Data Out no code
18 - Dataset Resources no code Blog Post
20 - Prepare Training Module for Spam + Not Spam
21 - Train Spam Classifier with SVC
23 - Scoring Classifier Accuracy
24 - One Hot Encoding Classification Recap
25 - Preprocessing with a Keras Tokenizer
27 - Convert Our Text Data into Sequences
29 - Reusable Text-Label Utility
30 - Split Training and Validation Data