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Introduction to the Python Deep Learning Library Theano
Last Updated on August 19, 2019 Theano is a Python library for fast numerical computation that can be run on the CPU or GPU. It is a key foundational library for Deep Learning in Python that you can u...
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Debugging Theano: FAQ and Troubleshooting
Debugging Theano: FAQ and Troubleshooting There are many kinds of bugs that might come up in a computer program. This page is structured as a FAQ. It provides recipes to tackle common problems, and i...
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Hands-On Theano: One of the Most Powerful Scientific Tools for Python
In my previous article, I mentioned 13 Data Science libraries for Python and I also talked about Theano. But that was a brief introduction, today we will talk more specifically about Theano, its…
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Profiling Theano function
Profiling Theano function Note This method replace the old ProfileMode. Do not use ProfileMode anymore. Besides checking for errors, another important task is to profile your code in terms of speed a...
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PyTorch -A Framework for Deep Learning
Deep learning is a subset of machine learning where artificial neural networks, algorithms inspired by the human brain, learn from large amounts of data. Every once in while, there comes a library or…...
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ONNX: The Standard for Interoperable Deep Learning Models
Learn about the benefits of using the ONNX standard for deploying models across frameworks and hardware platforms Continue reading on Towards Data Science
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Not Just PyTorch and TensorFlow: 4 Other Deep Learning Libraries You Should Lnow
A quick introduction to JAX, MXNet, MATLAB, and Flux Photo by Gabriel Sollmann on Unsplash Machine learning libraries accelerate the deep learning revolution. They lowered the barrier of entry for pr...
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Getting Started with TensorFlow the Easy Way (Part 1)
Given the recent spike in interest in the deep learning field, there is often a fiery debate that happens among data scientists — which framework is the best? This, like so many other things in this…
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Appendix: Tools for Deep Learning
To get the most out of Dive into Deep Learning , we will talk you through different tools in this appendix, such as for running and contributing to this interactive open-source book.
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Programming a Neural Network Tutorial: Vintage Style
Times Change (Abstraction) The code, tools, platforms, and related methods available to Widrow were not the code, tools, platforms, and related methods we have today. A relatively simple neural networ...
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A Beginner-Friendly Guide to PyTorch and How it Works from Scratch
Every once in a while, there comes a library or framework that reshapes and reimagines how we look at the field of deep learning. The remarkable progress a single framework can bring about never…
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Implementing RNNs
Hello everyone! This is my eleventh writing on my journey of Completing the Deep Learning Nanodegree in a month! I’ve done 51% of the fourth module out of a total of six modules of the degree. Today…
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A Brief History of Deep Learning Frameworks
A survey of deep learning frameworks and their future projection
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SRCNN Paper Summary & Implementation
SRCNN[1] proposes a 3 layer CNN for image super-resolution. It is one of the first papers to apply deep neural networks for the task of image super-resolution. The SRCNN architecture is composed of…
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10 GenAI Notebooks: OpenAI, LLM, RAG, GPT, and More
For developers and AI/ML professionals. This comprehensive free resource offered by our sponsor is designed to provide you with hands-on experience and deeper insights into building cutting-edge GenAI...
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Design an Easy-to-Use Deep Learning Framework
The three software design principles I learned as an open-source contributor Photo by Sheldon on Unsplash Deep learning frameworks are extremely transitory. If you compare the deep learning framework...
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☕️ 🕸 Deep Learning for Java and .NET Developers
📝 Editorial The deep learning space is mostly a Python game. Python’s flexibility and mathematically intuitive syntax have made it a favorite language of AI researchers and technologists producing a ...
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Fastai — the deep learning library that sits on top of Pytorch
TensorFlow and Pytorch are the most popular deep learning libraries of this moment. Besides that there are high level deep learning libraries. On top of Tensorflow there is Keras; a popular high…
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SRGAN, a TensorFlow Implementation
We’ve all seen that moment in a crime thriller where the hero asks the tech guy to zoom and enhance an image, number plates become readable, pixelated faces become clear and whatever evidence needed…
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Introduction to Python Deep Learning with Keras
Last Updated on September 13, 2019 Two of the top numerical platforms in Python that provide the basis for Deep Learning research and development are Theano and TensorFlow. Both are very powerful libr...
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Derivatives in Theano
Derivatives in Theano Computing Gradients Now let’s use Theano for a slightly more sophisticated task: create a function which computes the derivative of some expression y with respect to its paramet...
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Are You Sure That You Can Implement Image Classification Networks?
Before my recent paper submission, I firmly believed that I could easily implement image classification networks due to well-constructed… Continue reading on Towards AI
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Neural Network from Scratch (No NumPy)
Simple implementation of neural networks using standard Python library Continue reading on Towards Data Science
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The DataHour: Introduction to Tensorflow Javascript
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