NLP model selection guide to make it easier to select models. This is prescriptive in nature and has to be used with caution.

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2020-05-11 · This class will start with a brief overview of neural networks, then spend the majority of the class demonstrating how to apply neural networks to ...

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2020-06-25 · Expand the traditional EDA in a wider pipeline looking for the impact of each action into the behaviour of models. Exploratory Data & Models Analysis

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How can we efficiently train very deep neural network architectures? What are the best in-layer normalization options? Read on and find out.

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2020-05-01 · On-line interactive book introducing the history, theory, and math of Neural Network Models with Python, from a Cog Science perspective.

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A Tensorflow-based framework to ease the training of generative models

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2020-04-01 · Combine interpretability of a decision tree with accuracy of a neural network.

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This repository provides tutorial code in C++ to learn PyTorch by building CNNs, RNNs, etc. Tutorials are divided into three sections based on complexity.

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A book on data science and machine learning with a foundation in applied statistics leading into deep learning.

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