In this project I am asked to build machine learnings models for classifying text and to deploy them in a REST API (using Flask). A full description of the project is available here: https://github.com/eliaswalyba/digital-genius/blob/master/Machine%20Learning%20Engineer%20_%20Conversational%20AI%20Engineer%20-%20Technical.pdf
I actually proposed 6 models for this project and you can find all of them [here]:https://github.com/eliaswalyba/digital-genius/blob/master/models.ipynb
- Simple Statistical Learning Models 1.1. Multinomial Naive Bayes Classifier 1.2. Logistic Regression 1.3. Linear Support Vector Machines
- Pretrained Models 2.1. Word2Vec 2.2. Doc2Vec
- A simple Neural Network Using Keras
But before building the models I took some time to make exploratory data analysis with the dataset. You can find it [here]:https://github.com/eliaswalyba/digital-genius/blob/master/eda.ipynb
I also deployed the model using [Flask]:https://palletsprojects.com/p/flask/ and all the code is available in []: https://github.com/eliaswalyba/digital-genius/tree/master/webapp
- $ git clone https://github.com/eliaswalyba/digital-genius
- $ conda env create -f environment.yml
- $ cd digital-genius/webapp
- $ python app.py
For the 2 notebooks I suggest you open them using Google Colab (https://colab.research.google.com/)
Elias W. BA
Machine Learning Enthusiast
😍