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pytorch-kaldi is a project for developing state-of-the-art DNN/RNN hybrid speech recognition systems. The DNN part is managed by pytorch, while feature extraction, label computation, and decoding are performed with the kaldi toolkit.
In this project is presented a simple method to train an MLP neural network for audio signals. The trained model can be exported on a Raspberry Pi (2 or superior suggested) to classify audio signal registered with USB microphone
Developed a deep learning model that allows trading firms to analyze large patterns of stock market data and look for possible permutations to increase returns and reduce risk. Trained the model using a Multilayer Perceptron Neural Network on a vast set of features that influence the stock market indices. Performed technical analysis using histo…
Multi class audio classification using Deep Learning (MLP, CNN): The objective of this project is to build a multi class classifier to identify sound of a bee, cricket or noise.