Tag: Data visualization

Feed: All - O'Reilly Media. Author: Courtney Allen. TV genome visualization (source: bluefin on Wikimedia Commons) Jay Jacobs will teach a two-day tutorial course on data analysis and machine learning for cybersecurity at the O'Reilly Security Conference, October 29 to November 1, 2017, in New York City. Early price ends September 14. Subscribe to the O'Reilly Security Podcast to examine the challenges and opportunities for security practitioners, with a focus on the people on the frontlines of security, working to build better defenses. Find us on Stitcher, iTunes, SoundCloud, RSS. In this episode of the Security Podcast, Courtney Nash, former ... Read More

Feed: All - O'Reilly Media. Author: Manu Jeevan, Suresh Chelladurai. Road signs (source: Pixabay) The full Jupyter Notebook for this post can be accessed here. Although there are many deep learning frameworks, including TensorFlow, Keras, Torch, and Caffe, Apache MXNet in particular is gaining popularity due to its scalability across multiple GPUs. In this blog post, we'll tackle a computer vision problem: classifying German traffic signs using a convolutional neural network. The network takes a color photo containing a traffic sign image as input, and tries to identify the type of sign. The full notebook can be found here In ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Vincent Granville. Monday newsletter published by Data Science Central. Previous editions can be found here.  The contribution flagged with a + is our selection for the picture of the week. Featured Resources and Technical Contributions Generative Adversarial Networks (GANs) - Engine and Applications +  Building Convolutional Neural Networks with Tensorflow  Dogs vs. Cats: Image Classification with Deep Learning using TensorFlow in Python  Neural Networks: Crash Course On Multi-Layer Perceptron  Data Science Simplified Part 7: Log-Log Regression Models  Combining Multiple Methods To Improve Time Series Prediction  Nice Generalization of the K-NN Clustering Algorithm - Also ... Read More

Feed: R-bloggers. Author: Easy Guides. simplyR is a web space where we’ll be posting practical and easy guides for solving real important problems using R programming language. As we aren’t fans of unnecessary complications, we’ll keep the content of our tutorials / R codes as simple as possible. Many tutorials are coming soon. Topics we love include: R programming Biostatistics Genomic data analysis Survival analysis Machine/statistical learning Data visualization Samples of our recent publications, on R & Data Science, are: If you want to contribute, read this: http://www.sthda.com/english/pages/contribute-to-sthda Related To leave a comment for the author, please follow the link ... Read More

Feed: R-bloggers. Author: Euthymios Kasvikis. INTRODUCTION The ggvis package is used to make interactive data visualizations. The fact that it combines shiny’s reactive programming model and dplyr’s grammar of data transformation make it a useful tool for data scientists. This package may allows us to implement features like interactivity, but on the other hand every interactive ggvis plot must be connected to a running R session.Before proceeding, please follow our short tutorial.Look at the examples given and try to understand the logic behind them. Then try to solve the exercises below using R and without looking at the answers. Then ... Read More

Feed: R-bloggers. Author: Roger Oberg. If you’ve read the book “R for Data Science” or plan to, now you can dive deeper with co-author and RStudio Master Instructor Garrett Grolemund, winner of the Excellence in CE Award at JSM 2017! This two day workshop provides a comprehensive overview of what is now called the Tidyverse, a core set of R packages that are essential to Data Science. You will visualize, transform, and model data in R and work with date-times, character strings, and untidy data formats. Along the way, you will learn to use the brightest stars in the tidyverse: ... Read More

Feed: MapD Blog - Thoughts on GPU databases, data visualization and integrated analytics. Author: Todd Mostak. Today, with great pride, MapD is announcing a partnership with the Harvard Center for Geographic Analysis (CGA). We will be working with CGA to build new geospatial functionality into the MapD Core database, to improve hydrological modeling and visualization and allow for more accurate flood prediction and water-supply estimation. By combining CGA’s geospatial expertise with our team’s knowledge of high-performance analytics, we hope to build MapD into an even better platform for analyzing data at scale. More details of the collaboration can be found ... Read More

Feed: R-bloggers. Author: Nosha Assare. Atmospheric air pollution is one of the most important environmental concerns in many countries around the world, and it is strongly affected by meteorological conditions. Accordingly, in this set of exercises we use openair package to work and analyze air quality and meteorological data. This packages provides tools to directly import data from air quality measurement network across UK, as well as tools to analyse and producing reports. In this exercise set we will import and analyze data from MY1 station which is located in Marylebone Road in London, UK. Answers to the exercises are ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Vincent Granville. Monday newsletter published by Data Science Central. Previous editions can be found here.  The contribution flagged with a + is our selection for the picture of the week. Featured Resources and Technical Contributions Data Science Simplified Part 6: Model Selection Methods +  Handbook of Neural Computation  Two Great Courses on Deep Learning and AI  Free Deep Learning Book (MIT Press)  27 Great Resources About Logistic Regression  Create PostgreSQL Database In Linux And Connect To R  Understanding Neural Network: A beginner’s guide  Data Science Simplified Part 3: Hypothesis Testing  Data Science Simplified ... Read More

Feed: R-bloggers. Author: Euthymios Kasvikis. INTRODUCTION The ggvis package is used to make interactive data visualizations. The fact that it combines shiny’s reactive programming model and dplyr’s grammar of data transformation make it a useful tool for data scientists. This package may allows us to implement features like interactivity, but on the other hand every interactive ggvis plot must be connected to a running R session. Before proceeding, please follow our short tutorial.Look at the examples given and try to understand the logic behind them. Then try to solve the exercises below using R and without looking at the answers ... Read More