deeplearn-rs

Deeplearn-rs is a deep neural network in Rust. It has currently implemented models such as MNIST handwritten digit recognition and char-rnn using LSTM. Layers that has already been implemented are Matrix multiply (fully connected), Add (for bias, for example), LSTM, Softmax, MSE loss and Cross entropy loss. deeplearn-rs have SGD and RMSProp as optimizers.

Deeplearn-rs provide utilities for working with data which includes images, TSV and CSV and raw text data and word embeddings. It also allows data types other than f32 and implements casting between arrays of primitive numeric types as well as more layer types such as Conv2d, Pooling and Dropout.

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Predictive Analytics Process Flow

For more information of predictive analytics process, please review the overview of each components in the predictive analytics process: data collection (data mining), data analysis, statistical analysis, predictive modeling and predictive model deployment.