- COVID-19 Visualized: The power of effective visualizations for pandemic storytelling - Mar 27, 2020.
Clear, succinct data visualizations can be powerful tools for telling stories and explaining phenomena. This article demonstrates this concept as relates to the COVID-19 pandemic.
- Geovisualization with Open Data - Jan 15, 2020.
In this post I want to show how to use public available (open) data to create geo visualizations in python. Maps are a great way to communicate and compare information when working with geolocation data. There are many frameworks to plot maps, here I focus on matplotlib and geopandas (and give a glimpse of mplleaflet).
- 5 Great New Features in Latest Scikit-learn Release - Dec 10, 2019.
From not sweating missing values, to determining feature importance for any estimator, to support for stacking, and a new plotting API, here are 5 new features of the latest release of Scikit-learn which deserve your attention.
- Vega-Lite: A grammar of interactive graphics - Dec 3, 2019.
Vega and Vega-lite follow in a long line of work that can trace its roots back to Wilkinson’s ‘The Grammar of Graphics.’ Since then VegaLite has come into existence, bringing high-level specification of interactive visualisations to the Vega-Lite world.
- Task-based effectiveness of basic visualizations - Nov 27, 2019.
This is a summary of a recent paper on an age-old topic: what visualisation should I use? No prizes for guessing “it depends!” Is this the paper to finally settle the age-old debate surrounding pie-charts??
- The Four Levels of Analytics Maturity - Mar 26, 2019.
We outline our four-step model to categorize how successfully a company uses analytics by its ability to show the analytics, uncover underlying trends, and take action based on them.
- Intro to Data Science for Managers - Nov 23, 2018.
This mindmap contains a condensed introduction to the key data science concepts and techniques that have revolutionized the business landscape and became essential for making beneficial data-driven decisions
- 5 Machine Learning Projects You Should Not Overlook, June 2018 - Jun 12, 2018.
Here is a new installment of 5 more machine learning or machine learning-related projects you may not yet have heard of, but may want to consider checking out!
- Virtual Training Events Without Leaving Your Desk - May 30, 2018.
Check out our lineup of upcoming virtual seminars, online learning courses, and customized training in your office. Space is limited, so reserve your seat early and score the best savings!
- 6 Tips for Effective Visualization with Tableau - May 29, 2018.
We analyse principles for effective data visualization in Tableau, including color gradients, avoiding crowded dashboards, Tableau marks and more.
- Training and Visualising Word Vectors - Jan 23, 2018.
In this tutorial I want to show how you can implement a skip gram model in tensorflow to generate word vectors for any text you are working with and then use tensorboard to visualize them.
- Creating Simple Data Visualizations as an Act of Kindness - Dec 12, 2017.
The field of data visualization is still quite young and evolving rapidly—and tools like the web and VR are continuing to expand the possibilities. So there is a lot of room for exploring new possibilities and creating new formats, as well as many examples of novel and amazing visualizations.
- Visualizing Convolutional Neural Networks with Open-source Picasso - Aug 1, 2017.
Toolkits for standard neural network visualizations exist, along with tools for monitoring the training process, but are often tied to the deep learning framework. Could a general, easy-to-setup tool for generating standard visualizations provide a sanity check on the learning process?
- Beautiful Python Visualizations: An Interview with Bryan Van de Ven, Bokeh Core Developer - Aug 1, 2017.
Read this insightful interview with Bokeh's core developer, Bryan Van de Ven, and gain an understanding of what Bokeh is, when and why you should use it, and what makes Bryan a great fit for helming this project.
- Top 15 Python Libraries for Data Science in 2017 - Jun 13, 2017.
Since all of the libraries are open sourced, we have added commits, contributors count and other metrics from Github, which could be served as a proxy metrics for library popularity.
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- The R Graph Gallery Data Visualization Collection - Oct 13, 2016.
Welcome to the R graph gallery, a collection of R graph examples, organized by chart type, searchable by R function, with reproducible code and explanation.
- The Great Algorithm Tutorial Roundup - Sep 20, 2016.
This is a collection of tutorials relating to the results of the recent KDnuggets algorithms poll. If you are interested in learning or brushing up on the most used algorithms, as per our readers, look here for suggestions on doing so!
- DuPont: Research Scientist/ Visualization Specialist – TRIAD - Apr 16, 2016.
Provide leadership and drive delivery of scientific data visualizations, including geospatial, bioinformatics, population, and weather, for DuPont Pioneer research reporting.
- TD: Sr. Manager, Visualization - Apr 13, 2016.
Seeking a Senior Manager, Visualization, as a key part of a dynamic, innovative team that develops statistical models, data mining/analytical solutions and visualization solutions, and engages in leading-edge analytical and modelling work.
- 4 Lessons for Brilliant Data Visualization - Mar 11, 2016.
Get some pointers on data visualization from a noted expert in the field, and gain some insight into creating your own brilliant visualizations by following these 4 lessons.
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- New Books on Text Mining, Visualization, Social Media Analysis - Feb 16, 2016.
New books on "Text Mining and Visualization with Open-Source Tools" and "Graph-Based Social Media Analysis" provide essential and up-to-date information on these key topics. Use code BZQ31 to save 20%.
- Three Simple Resolutions to Design Better DataViz - Jan 20, 2016.
Start your New Year off with resolutions to produce better data visualizations: visualize your data, remove chart legends, and try new things.
- Interview: David Kasik, Boeing on Data Analysis vs Data Analytics - Feb 23, 2015.
We discuss the impact of increasing amount of data on visualization, difference between Data Analysis and Data Analytics, motivation, trends, desired skills and more.
- Top /r/MachineLearning posts, Jan 11-17 - Jan 18, 2015.
SVMs, open source datasets, Bayesian decision theory, game AI, and deep learning visualizations are all featured in the past week's top /r/MachineLearning posts.
- Interview: Miriah Meyer, Univ. of Utah on the Art and Science of Visualization - Jan 12, 2015.
We discuss insights from the best paper at ACM AVI 2014, increasing interest in visualization, infographics, trends, challenges, advice and more.
- Interview: Ben Werther, CEO, Platfora on Why Big Data Needs Self-Service Tools - Dec 29, 2014.
We discuss the importance of self-service model for Big Data tools, Small Data vs. Big Data, unique advantages of Platfora, key enhancements in Platfora 4.0 and more.
- Analyze And Visualize Chatter from Nigeria Elections 2015 - Dec 16, 2014.
A visual listening open data platform helps to see the chatter around upcoming Nigeria 2015 election – facts, ideas, topics, issues, statistics, queries – in a bare minimum of words and beautiful imagery.
- IBM Watson Analytics – Will it Replace Data Scientists ? - Nov 11, 2014.
We review IBM Watson Analytics Beta version, the service which aims to provide an automated data scientist and intended for business users who want to move beyond spreadsheets for analysis .
- Automotive Customer Churn Prediction Results, part 2 - Sep 29, 2014.
Learn how to apply neural networks and self-organizing maps to visualize the macroscopic relationships between clients and the maintenance evolution of cars over the years.
- Interview: Leo Meyerovich, Graphistry on Browser-based Interactive Big Data Visualization - Jul 24, 2014.
- WordSwarm – Visualizing Word Trends in Periodicals - Jul 24, 2014.
Word clouds provide an intuitive way to visualize word-frequency in corpora and are easy to generate. WordSwarm is a new free tool for animating word clouds that show how buzz-words ebb and flow in chronologically ordered text such as journals, blogs, and even Google n-grams.
- Business Intelligence Innovation Summit 2014 Chicago: Day 2 Highlights - Jul 23, 2014.
Highlights from the presentations by Business Intelligence leaders from Netflix, Hyatt, GE Capital and University of Texas on day 2 of Business Intelligence Innovation Summit 2014 in Chicago.
- Interview: Marc Smith, Chief Social Scientist, Connected Action, on Why We Need Open Tools for Social Networks - Jul 14, 2014.
We discuss NodeXL impact stories, upcoming NodeXL features, importance of an open environment, future of social media analytics, advice for novice researchers and more.
- Top KDnuggets tweets, Jul 7-10: IBM #Watson Swear Filter; How Birth Year Influences Political Views - Jul 13, 2014.
Appropriate after #BrazilvsGermany - IBM #Watson gets a Swear Filter; How Birth Year Influences Political Views; Analytics methods that "think" like Humans; Why lists of experts in Statistics, Data Science rarely intersect.
- Business Analytics Innovation Summit 2014 Chicago: Day 2 Highlights - Jul 11, 2014.
Highlights from the presentations by Business Analytics leaders from State of Illinois, Navistar, BMO Harris Bank and McGraw Hill Education on day 2 of Business Analytics Innovation Summit 2014 in Chicago.
- Top KDnuggets tweets, Jun 20-22: Great visualization of English letters; Good list of R functions to manipulate data - Jun 23, 2014.
Great visualization: English letters in words; Good list of R functions to manipulate data; Watch: Practical Deep-Learning Lecture: Machine Perception and Applications; Wikipedia Usage Statistics - analyze this 4TB data set in AWS cloud.
- Big Data for Executives 2014: Day 2 Highlights - May 29, 2014.
Highlights from the presentations by Big Data experts from McKinsey Solutions, SAP, Techfetch, Weather Analytics on Day 2 of Big Data for Executives 2014.
- Is Data Scientist the right career path for you? Candid advice - Mar 28, 2014.
Candid advice from an industry veteran reveals the true picture behind the much-talked-about Data Scientist "glamour" and helps people have the right expectations for a Data Science career.