RNN in Python that you could use to predict your final grade in a course based on the grades you have received on various assessments:

rnn-example

import tensorflow as tf

# Define the input data
X = np.array([
  [10], # grade on first assessment
  [20], # grade on second assessment
  [30]  # grade on third assessment
])

# Define the target variable
y = np.array([
  [80]  # final grade in the course
])

# Define the RNN model
model = tf.keras.models.Sequential([
  tf.keras.layers.SimpleRNN(units=10, input_shape=(1, 1)),
  tf.keras.layers.Dense(units=1)
])

# Compile the model
model.compile(optimizer='adam', loss='mean_squared_error')

# Fit the model on the data
model.fit(X, y, epochs=100)

# Define the input data for which we want to make a prediction
X_test = np.array([
  [15], # grade on fourth assessment
  [25], # grade on fifth assessment
  [35]  # grade on sixth assessment
])

# Make predictions using the model
predictions = model.predict(X_test)

# Print the predictions
print(predictions)