IMDB Sentiment Classification with LSTM
Classify IMDB reviews as positive or negative using LSTM. Covers word-to-integer encoding, pad sequences, Embedding layer, LSTM, and binary classification.
Master Neural Networks, Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs/LSTMs), Computer Vision, and advanced architectures using PyTorch, TensorFlow, and Keras.
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Classify IMDB reviews as positive or negative using LSTM. Covers word-to-integer encoding, pad sequences, Embedding layer, LSTM, and binary classification.
Generate Shakespearean text using stacked LSTM in TensorFlow. Covers corpus cleaning, tokenization, sequence preparation, Embedding layer, and word prediction.
Generate poetry with TensorFlow and LSTM. Covers tokenization, sequence preparation, Embedding layers, stacked LSTM training, and next-word prediction.
Predict Google stock prices using a stacked LSTM in TensorFlow. Covers RNN concepts, MinMaxScaler, data windowing, LSTM layers, and time-series visualization.
Predict airline passenger numbers using an LSTM in TensorFlow. Covers time-series data preparation, MinMaxScaler, look-back windows, and LSTM regression.
Predict household power consumption for the next week using LSTM. Covers multivariate time-series preprocessing, MinMaxScaler, and multi-step LSTM forecasting.
Recognize human activities from accelerometer data using a 2D CNN. Covers data balancing, LabelEncoder, frame-based feature extraction, and confusion matrix.
Fine-tune BERT for IMDB movie review sentiment classification using ktrain. Covers Transformer architecture, BERT tokenization, and one-cycle fine-tuning.
Fine-tune DistilBERT for sentiment classification using ktrain. Covers text preprocessing, DistilBERT tokenization, one-cycle training, and model deployment.
Apply GloVe vectors for Twitter sentiment analysis in TensorFlow. Covers text preprocessing, GloVe embedding matrix, Conv1D model, and binary classification.
Classify objects using the pre-trained VGG-16 model in Keras. Covers VGG architecture, loading ImageNet weights, image preprocessing, and top-5 predictions.
Classify movie genres from poster images using a 2D CNN. Covers multi-label classification, ImageDataGenerator, Conv2D with BatchNorm, and sigmoid output.
Classify dog and cat images using a 2D CNN in TensorFlow 2.0. Covers VGG16 architecture, Dropout, BatchNormalization, ImageDataGenerator, and SGD optimizer.
Train a 2D Convolutional Neural Network on CIFAR-10 using TensorFlow 2.0. Covers Conv2D, MaxPooling, Dropout, model training, and confusion matrix evaluation.
Detect fraudulent credit card transactions using a 1D CNN in TensorFlow. Covers dataset balancing, StandardScaler, Conv1D, BatchNormalization, and MaxPool1D.
Detect breast cancer using a 1D CNN in TensorFlow 2.0. Covers Conv1D, BatchNormalization, Dropout, Adam optimizer, and binary classification on medical data.
Predict bank customer satisfaction using a 1D CNN in TensorFlow. Covers feature selection, StandardScaler, Conv1D layers, and binary classification training.
Build your first ANN with TensorFlow 2.0 and Keras. Covers activation functions, optimizers, backpropagation, and binary classification on tabular data.
Get started with TensorFlow 2.0 by classifying Fashion MNIST images. Covers sequential models, Dense layers, ReLU activation, training, and prediction.
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Neural Networks, TensorFlow, ANN, CNN, RNN, LSTM, Transfer Learning and Much More.