- A Breakdown of Deep Learning Frameworks - Sep 23, 2021.
Deep Learning continues to evolve as one of the most powerful techniques in the AI toolbox. Many software packages exist today to support the development of models, and we highlight important options available with key qualities and differentiators to help you select the most appropriate for your needs.
Deep Learning, Keras, MATLAB, MXNet, PyTorch, TensorFlow
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.
Caffe, Deep Learning, GitHub, MXNet, Python, PyTorch, TensorFlow, Theano
- Deep Learning Framework Power Scores 2018 - Sep 24, 2018.
Who’s on top in usage, interest, and popularity?
CNTK, Deep Learning, fast.ai, Java, Keras, MXNet, Python, PyTorch, TensorFlow, Theano
- A Crash Course in MXNet Tensor Basics & Simple Automatic Differentiation - Aug 16, 2018.
This is an overview of some basic functionality of the MXNet ndarray package for creating tensor-like objects, and using the autograd package for performing automatic differentiation.
GPU, MXNet, Python, Tensor
- 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.
Caffe, CNTK, Deep Learning, GPU, Keras, Microsoft, MXNet, PyTorch, TensorFlow
5 Fantastic Practical Machine Learning Resources - Feb 6, 2018.
This post presents 5 fantastic practical machine learning resources, covering machine learning right from basics, as well as coding algorithms from scratch and using particular deep learning frameworks.
Deep Learning, fast.ai, Gluon, Machine Learning, MOOC, MXNet, Python
