Python for Text Classification
Python for Text Classification with Machine Learning in Python 3.6.
Installation Guide
Start your environment by picking either pipenv (recommended) or virtualenv. Simple guides are below.
Using pipenv
- 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
Using virtualenv
- 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
Lessons
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