Text Classification:

• IMDB Sentiment Analysis: Using Keras for binary sentiment classification (positive/negative) on the IMDB movie review dataset with recurrent neural networks (RNNs) or LSTMs.

pythonCopy codefrom tensorflow.keras.datasets import imdb
from tensorflow.keras.preprocessing import sequence
from tensorflow.keras import layers, models

# Load IMDB dataset
max_features = 10000
(x_train, y_train), (x_test, y_test) = imdb.load_data(num_words=max_features)

# Pad sequences to ensure uniform input size
maxlen = 500
x_train = sequence.pad_sequences(x_train, maxlen=maxlen)
x_test = sequence.pad_sequences(x_test, maxlen=maxlen)

# Build LSTM model
model = models.Sequential([
    layers.Embedding(max_features, 128, input_length=maxlen),
    layers.LSTM(128, dropout=0.2, recurrent_dropout=0.2),
    layers.Dense(1, activation='sigmoid')
])

# Compile and train the model
model.compile(optimizer='adam', loss='binary_crossentropy', metrics=['accuracy'])
model.fit(x_train, y_train, epochs=3, batch_size=64, validation_data=(x_test, y_test))