Learn how to create a simple neural network, and a more accurate convolutional neural network, with the PyTorch deep learning library
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We rank 23 open-source deep learning libraries that are useful for Data Science. The ranking is based on equally weighing its three components: Github and Stack Overflow activity, as well as Google search results.
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Deep Learning is a collection of algorithms used in machine learning. This is an approach used for building and training neural network. There are many frameworks like Tensorflow, Theono, Caffe, Torch and PyTorch.
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Scholarship recipients will learn the Machine Learning, Deep Learning framework PyTorch for Artificial Intelligence Research.
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Speech recognition is the task of detecting spoken words. There are many techniques to do Speech Recognition. In this post, we will go through some background required for Speech Recognition and use a basic technique to build a speech recognition model. The code is available on GitHub. For the techniques mentioned in this post, check this Jupyter Notebook.
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GitHub has identified three features that make a programming language popular in 2018.
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We will now talk about what are some steps that you can do if you want to deploy your recently trained model as an API. The discussion on how to do this with Fast.ai is currently ongoing (more) and will most likely continue until PyTorch releases their official 1.0 version. You can find more information in the Fast.ai Forums, PyTorch Documentation/Forums, and their respective GitHub repositories.
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More than 1,300 people mainly working in the tech, finance, and healthcare revealed which machine-learning technologies they use at their firms, in a new O'Reilly survey.
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Using a Deep Learning Framework Deep Learning models are easily developed by the professionals without requiring to develop the models from starting.
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Well-architected API on top of either Tensorflow or Theano and potentially extensible as a shim over other deep learning engines as well.
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Natural Language Processing (NLP) is a very important field in the present time. The present article is an amalgamation of some of the most useful books with some of the amazing YouTube videos available online which you can easily refer for NLP.
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Facebook's commitment to the wider dev community remains as strong as ever if recent developments are any indication.
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Artificial Intelligence (AI) is a field that has a long history but is still constantly and actively growing and changing. Here are some courses which will make you aware of everything about this technology.
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Each chapter focuses on a different area of deep learning. Chapters start with a refresher on the core principles, before sharing the code you need to implement them in PyTorch.
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Machine Learning is invading this world gradually and gradually. If we can develop a driverless car then it is Machine Learning.
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In this article, you will get to know some of the best frameworks to get you started with AI development.
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Accelerate your deep learning with PyTorch covering all the fundamentals of deep learning with a python-first framework.
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Fortunately, some brilliant minds have created and generously open-sourced several deep learning frameworks that can be easily integrated by people with little to no knowledge of machine learning technology.
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Here are some resources to learn deep learning frameworks.
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Machine learning is the buzzword bringing computer science and statistics together to build smart and efficient models. Here are some famous machine learning tools to learn from some famous books.
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