Machine Learning in Python

Don't forget to :

$ source ./venv/bin/activate

(to create venv : python3 -m venv venv)

To install dependancies

$ pip install -r requirements.txt

Machine learning

Simple Perceptron

$ python src/perceptron/perceptron_ui.py

Press s to start the perceptron

Press q to quit the perceptron

TensorFlow Perceptron

WORK IN PROGRESS

$ python src/perceptron/perceptron_tf.py

Neural Network

Running the neural network base configuration with XOR classification.

$ python src/neural_network/xor_basic.py

Running the neural network with XOR classification with render system made with Matplotlib and Tk.

$ python src/neural_network/xor_plt.py
$ python src/neural_network/xor_tk.py

Running the neural network doodle classifier using Google Quickdraw dataset.

$ python src/neural_network/doodle_classifier.py

https://quickdraw.withgoogle.com/
https://github.com/googlecreativelab/quickdraw-dataset
https://console.cloud.google.com/storage/browser/quickdraw_dataset

Genetic Algorithm

$ python src/genetic_algorithm.py

Natural Langage Processing

https://rasa.com/products/rasa-stack/
https://github.com/RasaHQ/starter-pack-rasa-nlu

Project initialization:

$ cd src/nlp
$ pip install -r requirements.txt

Loading language model:

$ python -m spacy download en

Training the model:

$ python -m rasa_nlu.train -c data/nlu_config.yml --data data/data.md -o data/models --project test_en

Run nlu model as a server:

$ python -m rasa_nlu.server --path data/models

To query the server:

$ curl -X POST localhost:5000/parse -d '{"query": "Hello", "project": "test_en"'

Advanced algorithms

Maze solving

WORK IN PROGRESS