- How to deploy Machine Learning/Deep Learning models to the web [Gold Blog]
The full value of your deep learning models comes from enabling others to use them. Learn how to deploy your model to the web and access it as a REST API, and begin to share the power of your machine learning development with the world.
- 10 Amazing Machine Learning Projects of 2020 [Silver Blog]
So much progress in AI and machine learning happened in 2020, especially in the areas of AI-generating creativity and low-to-no-code frameworks. Check out these trending and popular machine learning projects released last year, and let them inspire your work throughout 2021.
- Evaluating Deep Learning Models: The Confusion Matrix, Accuracy, Precision, and Recall [Gold Blog]
This tutorial discusses the confusion matrix, and how the precision, recall and accuracy are calculated, and how they relate to evaluating deep learning models.
- Approaching (Almost) Any Machine Learning Problem [Silver Blog]
This freely-available book is a fantastic walkthrough of practical approaches to machine learning problems.
- Deep learning doesn’t need to be a black box [Silver Blog]
The cultural perception of AI is often suspect because of the described challenges in knowing why a deep neural network makes its predictions. So, researchers try to crack open this "black box" after a network is trained to correlate results with inputs. But, what if the goal of explainability could be designed into the network's architecture -- before the model is trained and without reducing its predictive power? Maybe the box could stay open from the beginning.
- Building a Deep Learning Based Reverse Image Search [Silver Blog]
Following the journey from unstructured data to content based image retrieval.
- DeepMind’s MuZero is One of the Most Important Deep Learning Systems Ever Created [Gold Blog]
MuZero takes a unique approach to solve the problem of planning in deep learning models.
- 15 Free Data Science, Machine Learning & Statistics eBooks for 2021 [Platinum Blog]
We present a curated list of 15 free eBooks compiled in a single location to close out the year.
- AI, Analytics, Machine Learning, Data Science, Deep Learning Research Main Developments in 2020 and Key Trends for 2021 [Silver Blog]
2020 is finally coming to a close. While likely not to register as anyone's favorite year, 2020 did have some noteworthy advancements in our field, and 2021 promises some important key trends to look forward to. As has become a year-end tradition, our collection of experts have once again contributed their thoughts. Read on to find out more.
- Learn Deep Learning with this Free Course from Yann LeCun [Gold Blog]
Here is a freely-available NYU course on deep learning to check out from Yann LeCun and Alfredo Canziani, including videos, slides, and other helpful resources.
- Facebook Open Sourced New Frameworks to Advance Deep Learning Research [Silver Blog]
Polygames, PyTorch3D and HiPlot are the new additions to Facebook’s open source deep learning stack.
- Top Python Libraries for Deep Learning, Natural Language Processing & Computer Vision [Gold Blog]
This article compiles the 30 top Python libraries for deep learning, natural language processing & computer vision, as best determined by KDnuggets staff.
- How to Acquire the Most Wanted Data Science Skills [Gold Blog]
We recently surveyed KDnuggets readers to determine the "most wanted" data science skills. Since they seem to be those most in demand from practitioners, here is a collection of resources for getting started with this learning.
- Top 5 Free Machine Learning and Deep Learning eBooks Everyone should read [Gold Blog]
There is always so much new to learn in machine learning, and keeping well grounded in the fundamentals will help you stay up-to-date with the latest advancements while acing your career in Data Science.
- Building Neural Networks with PyTorch in Google Colab [Silver Blog]
Combining PyTorch and Google's cloud-based Colab notebook environment can be a good solution for building neural networks with free access to GPUs. This article demonstrates how to do just that.
- An Introduction to AI, updated [Silver Blog]
We provide an introduction to key concepts and methods in AI, covering Machine Learning and Deep Learning, with an updated extensive list that includes Narrow AI, Super Intelligence, and Classic Artificial Intelligence, as well as recent ideas of NeuroSymbolic AI, Neuroevolution, and Federated Learning.
- PerceptiLabs – A GUI and Visual API for TensorFlow [Gold Blog]
Recently released PerceptiLabs 0.11, is quickly becoming the GUI and visual API for TensorFlow. PerceptiLabs is built around a sophisticated visual ML modeling editor in which you drag and drop components and connect them together to form your model, automatically creating the underlying TensorFlow code. Try it now.
- 10 Best Machine Learning Courses in 2020 [Gold Blog]
If you are ready to take your career in machine learning to the next level, then these top 10 Machine Learning Courses covering both practical and theoretical work will help you excel.
- Implementing a Deep Learning Library from Scratch in Python [Silver Blog]
A beginner’s guide to understanding the fundamental building blocks of deep learning platforms.
- Autograd: The Best Machine Learning Library You’re Not Using? [Gold Blog]
If there is a Python library that is emblematic of the simplicity, flexibility, and utility of differentiable programming it has to be Autograd.
- Deep Learning’s Most Important Ideas [Gold Blog]
In the field of deep learning, there continues to be a deluge of research and new papers published daily. Many well-adopted ideas that have stood the test of time provide the foundation for much of this new work. To better understand modern deep learning, these techniques cover the basic necessary knowledge, especially as a starting point if you are new to the field.