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Basic to Advance Tensorflow codes for Artificial Intelligence and Machin learning
tensorflow's Introduction
TensorFlow Basic to Advance Conncept and codes
- Concept 1: Defining tensors
- Concept 2: Evaluating ops
- Concept 3: Interactive session
- Concept 4: Session loggings
- Concept 5: Variables
- Concept 6: Saving variables
- Concept 7: Loading variables
- Concept 8: TensorBoard
- Concept 1: Linear regression
- Concept 2: Polynomial regression
- Concept 3: Regularization
- Concept 1: Linear regression for classification
- Concept 2: Logistic regression
- Concept 3: 2D Logistic regression
- Concept 4: Softmax classification
- Concept 1: Clustering
- Concept 2: Segmentation
- Concept 3: Self-organizing map
- Concept 1: Forward algorithm
- Concept 2: Viterbi decode
- Concept 1: Autoencoder
- Concept 2: Applying an autoencoder to images
- Concept 3: Denoising autoencoder
- Concept 1: Reinforcement learning
- Concept 1: Using CIFAR-10 dataset
- Concept 2: Convolutions
- Concept 3: Convolutional neural network
- Concept 1: Loading timeseries data
- Concept 2: Recurrent neural networks
- Concept 3: Applying RNN to real-world data for timeseries prediction
- Concept 1: Multi-cell RNN
- Concept 2: Embedding lookup
- Concept 3: Seq2seq model
- Concept 1: RankNet
- Concept 2: Image embedding
- Concept 3: Image ranking
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