Open Source libraries
Jon Krohn at the New-York R confenrence (libraries for Data Science)
- igraph (R, python, Mathematica & C++)
- targets (R, successor of drake [for python snakemake])
- janitor (R, cleaner)
- dplyr (R, intuitive data analysis)
Machine learning on quantum hardware. Connect to quantum hardware using PyTorch, TensorFlow, JAX, Keras, or NumPy. Build rich and flexible hybrid quantum-classical models.
Good to try on AWS Bracket
The attention mechanism, initially used in natural language processing fields, has found its way into finance and other domains. It operates on a simple concept: some parts of the input sequence are more important then others. The attention mechanism improve models and understand's capabilities, by allowing the model to focus on specific parts of the input sequence while ignoring others.
Incorporating attention into LSTM networks give a context to the model for predictions, certain historical data points may be more relevant than others. The attention mechanism give the LSTM ability to weigh these points more heavily, leading to more accurate and nuanced predictions.
Prepare de Data ...
from keras.models import Sequential
from keras.layers import LSTM, Dense, Dropout, AdditiveAttention, Permute, Reshape, Multiply
model = Sequential()
model.add(LSTM(units=50, return_sequences=True, input_shape=(X_train.shape[1], 1)))
model.add(LSTM(units=50, return_sequences=True, name="lstm_layer"))
attention = AdditiveAttention()
attention_result = attention([model.outputs[0], model.outputs[0]])
attention_result = Multiply()([model.outputs[0], attention_result])
model.add(tf.keras.layers.Flatten())
model.add(Dense(1))
Add the Dropout and BatchNormalization before Compiling ...
Train, Predict and Visualize
Create the service file:
[Unit]
Description=daphne daemon
Requires=daphne.socket
After=network.target
[Service]
Type=simple
User=user_name
WorkingDirectory=/var/www/app_name
ExecStart=/home/user_name/python_env/bin/daphne -u /tmp/daphne.sock app_name.asgi:application
[Install]
WantedBy=multi-user.target
Command lines:
sudo systemctl start daphne.service
sudo systemctl stop daphne.service
sudo systemctl restart daphne.service
sudo systemctl status daphne.service
Change the specified port:
Restart the deamon:
Change the port and verify:
Ask access to firewall:
If you're on a VPS with a firewall, give access to the port