Deep Learning / learning techniques

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Using Deep Learning techniques to enhance orthology calls

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Deep learning simplified by transferring prior learning using the Python deep learning ecosystem

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Code repository for Python Deep Learning Second Edition, published by Packt

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(no description)

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Master the essential skills needed to recognize and solve complex real-world problems with Machine Learning and Deep Learning by leveraging the highly popular Python Machine Learning Eco-system.

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Implementations of (Deep Learning + Machine Learning) Algorithms

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Python Deep Learning Second Edition, Published by Packt

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As a graduate majoring in Economics and Finance, I combined my passion of capital market with newly acquired programming skills for an end to end machine learning projects, from crawling data, model testing and writing reports based on latest literature

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A collection of several Deep Reinforcement Learning techniques (Deep Q Learning, Policy Gradients, ...), gets updated over time.

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Implemented the deep learning techniques using Google Tensorflow that cover deep neural networks with a fully connected network using SGD and ReLUs; Regularization with a multi-layer neural network using ReLUs, L2-regularization, and dropout, to prevent overfitting; Convolutional Neural Networks (CNNs) with learning rate decay and dropout; and Recurrent Neural Networks (RNNs) for text and sequences with Long Short-Term Memory (LSTM) networks.

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