Posts published in “Tutorials”

Querying Data in Spreadsheets, No Database Required

Published September 25, 2016 by Ryan O'Shea

Querying Data in Spreadsheets, No Database Required

When you’re working with lots of data, few tools are more useful than a powerful querying language like SQL. The ability to isolate the data you’re looking for, make useful transformations, and generate statistics…

Zoom with Composable!

Published January 26, 2016 by Lars Fiedler

Zoom with Composable!

We’re proud to announce Composable’s data flow designer now supports full zooming and panning! We think this feature will make working larger more complicated CA apps much easier. Over the…

Monash University: Research Fellow – Optimisation [Melbourne, Australia]
Seeking an enthusiastic researcher with solid skills in any of the following areas: constraint programming, mixed integer programming, SAT and SAT modulo theories, modelling languages and program analysis, to join an established team working on new approaches to modelling and solving discrete optimisation problems.
Think Like an Amateur, Do As an Expert: Lessons from a Career in Computer Vision
Dr. Takeo Kanade shared his life lessons from an illustrious 50-year career in Computer Vision at last year's Embedded Vision Summit. You have a chance to attend the 2019 Embedded Vision Summit, from May 20-23, in the Santa Clara Convention Center, Santa Clara CA.
60+ useful graph visualization libraries
We outline 60+ graph visualization libraries that allow users to build applications to display and interact with network representations of data.
PyCharm for Data Scientists
This article is a discussion of some of PyCharm's features, and a comparison with Spyder, an another popular IDE for Python. Read on to find the benefits and drawbacks of PyCharm, and an outline of when to prefer it to Spyder and vice versa.
7 Steps to Mastering SQL for Data Science — 2019 Edition
Follow these updated 7 steps to go from SQL data science newbie to practitioner in a hurry. We consider only the necessary concepts and skills, and provide quality resources for each.
A complete guide to K-means clustering algorithm
Clustering - including K-means clustering - is an unsupervised learning technique used for data classification. We provide several examples to help further explain how it works.
Why Data Professionals Should Negotiate Every Job Offer
Here are six reasons why you shouldn't feel tempted to jump at the chance and take that job offer as it is without first negotiating.
Large-Scale Evolution of Image Classifiers
Deep neural networks excel in many difficult tasks, given large amounts of training data and enough processing power. The neural network architecture is an important factor in achieving a highly accurate model... Techniques to automatically discover these neural network architectures are, therefore, very much desirable.
Top KDnuggets tweets, May 08-14: The end of average Data Scientist is near: @GoogleAI fully automated, End-to-End #AutoML #MachineLearning
Also: My favorite free courses to learn data structures and #algorithms in depth; “Please, explain.” Interpretability of machine learning models; Decoding ‘A Game of Thrones’ #GOT with data science; Another 10 Free Must-See Courses for Machine Learning and Data Science; Best Data Visualization Techniques for small and large data
Building Recommender systems with Azure Machine Learning service
Microsoft has provided a GitHub repository with Python best practice examples to facilitate the building and evaluation of recommendation systems using Azure Machine Learning services.