- 5 Data Science Open-source Projects You Should Consider Contributing to - Jun 7, 2021.
As you prepare to interview for a position in data science or are looking to jump to the next level, now is the time to enhance your skills and your resume with by working on rea, open-source projects. Here, we suggest a great selection of projects you can contribute to and help build something awesome, so, all you need to do choose one and tackle it head on.
- Top 13 Python Deep Learning Libraries - Nov 2, 2018.
Part 2 of a new series investigating the top Python Libraries across Machine Learning, AI, Deep Learning and Data Science.
- Ultra-compact workstation for top deep learning frameworks - Apr 27, 2018.
For workstation development platforms purpose-built for Tensorflow, PyTorch, Caffe2, MXNet, and other DL frameworks, the solution is BOXX. We're bringing deep learning to your deskside with the all-new APEXX W3!
- Top 16 Open Source Deep Learning Libraries and Platforms - Apr 24, 2018.
We bring to you the top 16 open source deep learning libraries and platforms. TensorFlow is out in front as the undisputed number one, with Keras and Caffe completing the top three.
- Comparing Deep Learning Frameworks: A Rosetta Stone Approach - Mar 26, 2018.
A Rosetta Stone of deep-learning frameworks has been created to allow data-scientists to easily leverage their expertise from one framework to another.
- Choosing an Open Source Machine Learning Library: TensorFlow, Theano, Torch, scikit-learn, Caffe - Nov 8, 2017.
Open Source is the heart of innovation and rapid evolution of technologies, these days. Here we discuss how to choose open source machine learning tools for different use cases.
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- Ranking Popular Deep Learning Libraries for Data Science - Oct 23, 2017.
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.
- Getting Started with Deep Learning - Mar 24, 2017.
This post approaches getting started with deep learning from a framework perspective. Gain a quick overview and comparison of available tools for implementing neural networks to help choose what's right for you.
- Top KDnuggets tweets, Jun 29 – Jul 5: Big Data Ecosystem is Too Damn Big!; Deep Learning Intro with Caffe and Python - Jul 6, 2016.
The #BigData Ecosystem is Too Damn Big!; A Practical Introduction to #DeepLearning with Caffe and #Python; What do Postgres, Kafka, and Bitcoin have in common?
- Yahoo! CaffeOnSpark: Distributed Deep Learning on Big Data Clusters - Feb 29, 2016.
Get an overview of Yahoo!'s CaffeOnSpark, the latest entrant into the world of distributed deep learning, directly from the developers.
- Opening Up Deep Learning For Everyone - Feb 19, 2016.
Opening deep learning up to everyone is a noble goal. But is it achievable? Should non-programmers and even non-technical people be able to implement deep neural models?
- Top 10 Deep Learning Projects on Github - Jan 13, 2016.
The top 10 deep learning projects on Github include a number of libraries, frameworks, and education resources. Have a look at the tools others are using, and the resources they are learning from.
- 7 Steps to Understanding Deep Learning - Jan 11, 2016.
There are many deep learning resources freely available online, but it can be confusing knowing where to begin. Go from vague understanding of deep neural networks to knowledgeable practitioner in 7 steps!
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- 50 Deep Learning Software Tools and Platforms, Updated - Dec 15, 2015.
We present the popular software & toolkit resources for Deep Learning, including Caffe, Cuda-convnet, Deeplearning4j, Pylearn2, Theano, and Torch. Explore the new list!
- Spark + Deep Learning: Distributed Deep Neural Network Training with SparkNet - Dec 4, 2015.
Training deep neural nets can take precious time and resources. By leveraging an existing distributed batch processing framework, SparkNet can train neural nets quickly and efficiently.
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- 7 Steps to Mastering Machine Learning With Python - Nov 19, 2015.
There are many Python machine learning resources freely available online. Where to begin? How to proceed? Go from zero to Python machine learning hero in 7 steps!
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- Deep Learning and Artistic Style – Can art be quantified? - Sep 17, 2015.
We analyze the latest advance in Deep learning which teaches computers to paint in the style of different famous painters, from Van Gogh to Picasso. Is it really Art?