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Optimizing PyTorch Performance: Batch Size with PyTorch Profiler
This tutorial demonstrates a few features of  PyTorch Profiler that have been released in v1.9. PyTorch. Profiler is a set of tools that allow you to measure the training performance and resource consumption of your PyTorch model. This tool will help you diagnose and fix machine learning performance issues regardless of whether you are working on one or... Read more
Ten Trending Data Science Tools in 2021
The fields of data science and artificial intelligence see constant growth. As more companies and industries find value in automation, analytics, and insight discovery, there comes a need for the development of new tools, frameworks, and libraries to meet increased demand. There are some tools that... Read more
Implementing Content-Based Image Retrieval with Siamese Networks in PyTorch
Image retrieval is the task of finding images related to a given query. With content-based image retrieval, we refer to the task of finding images containing some attributes which are not in the image metadata, but present in its visual content. In this post we: –... Read more
Autograd is PyTorch’s automatic differentiation package. Thanks to it, we don’t need to worry about partial derivatives, chain rule, or anything like it. To illustrate how it works, let’s say we’re trying to fit a simple linear regression with a single feature x, using Mean Squared... Read more
10 Notable Frameworks for NLP
Natural Language Processing hit its big stride back in 2017 with the introduction of Transformer Architecture from Google. State of the art approaches helped bridge the gap between humans and machines and helped us build bots capable of using human language undetected. It’s an exciting time.... Read more
Major Updates to the Most Popular Data Science Frameworks in 2019
This time last year we brought you a detailed report of all the important updates for popular data science (machine learning and deep learning) frameworks throughout 2018. The developers of these frameworks continue to innovate at an accelerated rate. Data scientists demand more powerful tools in... Read more
Top 7 Machine Learning Frameworks for 2020
Machine learning is a nightmare without some kind of structure. You can’t build everything from scratch, especially if you’re in a business setting. Even if you want to (and if you do, comment here and tell us about it!), you don’t have time in most cases.... Read more
Deep Learning Frameworks You Need to Know in 2020
Deep learning networks have a mind-boggling ability to learn, so training these models requires massive computing power and intense amounts of data. You’ll need a framework to make that development easier. Deep learning requires massive processing power and lots of data. Because it uses unstructured, often non-text... Read more
RAPIDS 0.8: Same Community New Freedoms
RAPIDS released 0.8 a few weeks back. And afterwards, like most Americans, we took off for the 4th of July holiday. Over that break, I reflected on the purpose of RAPIDS. Speed is great, building a strong community is awesome, but the true power of RAPIDS is... Read more
Exploring the Deep Learning Framework PyTorch
There are a variety of open-source deep learning frameworks to choose from including Keras, TensorFlow, Caffe2, and MXNet among others. At ODSC West in 2018, Stephanie Kim, a developer at Algorithmia, gave a great talk introducing the deep learning framework PyTorch. Primarily developed by Facebook, PyTorch... Read more