Matthew Mayo (@mattmayo13) is a Data Scientist and the Editor-in-Chief of KDnuggets, the seminal online Data Science and Machine Learning resource. His interests lie in natural language processing, algorithm design and optimization, unsupervised learning, neural networks, and automated approaches to machine learning. Matthew holds a Master's degree in computer science and a graduate diploma in data mining. He can be reached at editor1 at kdnuggets[dot]com.
The recent open sourcing of Google's TensorFlow was a significant event for machine learning. While the original release was lacking in some ways, development continues and improvements are already being made.
The top 10 machine 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.
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.
November on /r/DataScience: Plot.ly is open sourced, Pokemon and Big Data games, a new social network analysis package for R, insider information on landing a Google Data Scientist job, and a free data science curriculum.
In November on /r/MachineLearning, we've got a good laugh, a fantastic image-generating convolutional generative adversarial network, and a whole lot of Google TensorFlow.
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!
Google recently open-sourced its TensorFlow machine learning library, which aims to bring large-scale, distributed machine learning and deep learning to everyone. But does it deliver?
Machine learning video lectures, deep nets evaluate selfies, Google focusing on machine learning, DeepMind's huge text dataset made available, implement a recurrent neural net, and open source face recognition with Google's FaceNet.
MIT researchers have developed what they refer to as the Data Science Machine, which combines feature engineering and an end-to-end data science pipeline into a system that beats nearly 70% of humans in competitions. Is this game-changing?
Matthew Mayo (@mattmayo13) is a Data Scientist and the Editor-in-Chief of KDnuggets, the seminal online Data Science and Machine Learning resource. His interests lie in natural language processing, algorithm design and optimization, unsupervised learning, neural networks, and automated approaches to machine learning. Matthew holds a Master's degree in computer science and a graduate diploma in data mining. He can be reached at editor1 at kdnuggets[dot]com.
Top 10 Machine Learning Projects on Github
