22 free tools for data visualization and analysis
You may not think you've got much in common with an investigative journalist or an academic medical researcher. But if you're trying to extract useful information from an ever-increasing inflow of data, you'll likely find visualization useful -- whether it's to show patterns or trends with graphics instead of mountains of text, or to try to explain complex issues to a nontechnical audience. There are many tools around to help turn data into graphics, but they can carry hefty price tags. The cost can make sense for professionals whose primary job is to find meaning in mountains of information, but you might not be able to justify such an expense if you or your users only need a graphics application from time to time, or if your budget for new tools is somewhat limited. If one of the higher-priced options is out of your reach, there are a surprising number of highly robust tools for data visualization and analysis that are available at no charge.
HBase
www.tuaw.com/about
Established December 5, 2004, The Unofficial Apple Weblog (TUAW) is a resource for all things Apple and beyond. TUAW publishes news stories, credible rumors and how-to's covering a variety of topics daily. As a trusted tech blog, TUAW provides opinion and analysis on the news in addition to the facts. TUAW is a trusted source for news, information and analysis about Apple and its products. Our readership is made up of new users, intermediate and business users and advanced users.
Big Data Is As Misunderstood As Twitter Was Back In 2008
Boonsri Dickinson, Business Insider In 2008, when Howard Lindzon started StockTwits, no one knew what Twitter was. Obviously, that has changed. Now that Twitter is more of a mainstream communication channel, Lindzon has figured out the secret to getting past all the noise on Twitter. By using human curation, StockTwits can serve up relevant social media content to major players like MSN Money. Lindzon said there are three key aspects that have helped solve the spammy nature of Twitter:
Apache Pig
Groovy - Home
Semantic Bits
What Machine Learning Can Do And What Machine Learning Cannot Do Posted by Stacy on 24-08-2018
Sqoop
The Jython Project
Deep learning based Object Detection and Instance Segmentation using Mask R-CNN in OpenCV (Python / C++)
A few weeks back we wrote a post on Object detection using YOLOv3. The output of an object detector is an array of bounding boxes around objects detected in the image or video frame, but we do not get any clue about the shape of the object inside the bounding box. Wouldn’t it be cool if we could find a binary mask containing the object instead of just the bounding box? In this post, we will learn how to do just that. We will show how to use a Convolutional Neural Network (CNN) model called Mask-RCNN (Region based Convolutional Neural Network) for object detection and segmentation. Using Mask-RCNN we not only detect the object, we also obtain a greyscale or binary mask containing the object.
Flume
A data warehouse system for Hadoop that offers a SQL-like query language to facilitate easy data summarization, ad-hoc queries, and the analysis of large datasets stored in Hadoop compatible file systems. by sergeykucherov Jul 15