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More on Fully Automated Machine Learning

Summary:  Recently we’ve been profiling Automated Machine Learning (AML) platforms, both of the professional variety, and particularly those proprietary one-click-to-model variety that are being pitched to untrained analysts and line-of-business managers.  Since our first article, readers have suggested some additional companies we should look at which are profiled here along with some interesting observations about who is buying and why.




Added by William Vorhies on August 15, 2017 at 2:21pm — No Comments

Manipulating and processing data in R

Manipulating and processing data in R

Data structures provide the way to represent data in data analytics. We can manipulate data in R for analysis and visualization.

One of the most important aspects of computing with data in R is its ability to manipulate data and enable its subsequent analysis and visualization. Let us see few basic data structures in R:

a. Vectors in R

These are…


Added by Shreya Gupta on August 11, 2017 at 12:00am — No Comments

Functions in R

R Introduction and Features

R is a free software programming language and software environment for statistical computing and graphics. The R language is widely used among statisticians and data miners for developing statistical software and data analysis and visualization.

Let us now look at some key capabilities of R:

  • R is easily extensible through functions and…

Added by Shreya Gupta on August 11, 2017 at 11:30pm — No Comments

Improving life with IoT and Analytics

Last weekend I went to attend one event hosted by GE digital in association with T-HUB and Idea labs.

The event was about industrial IoT and Predix Platform developed by GE Digital for IIOT.

It was a very much informative event, and I also had the privilege to meet some awesome people over there who are part of this platform development.

GE is the well-known company we all know.   

Now coming to the usage of IoT and analytics in this. GE Develops a lot of turbines…


Added by balram prasad on August 11, 2017 at 9:30pm — No Comments

Creating functions in R

Functions are used to simplify a series of calculations.

For instance, let us suppose that there exists an array of numbers which we wish to add to another variable. Instead of carrying out separate calculations for each number in the array, it would be much easier to simply create a function that does this for us automatically.

A function in R generally works by:

(a) Defining the variables to include in the function and the calculation. e.g. to add two…


Added by Michael Grogan on August 12, 2017 at 5:30am — No Comments

Sequenced Differential Lattices and Randomness

The images on this blog are from an algorithmic environment that I first developed about 15 years ago - rendered using a graphical system that I wrote in Java.  A “differential lattice” is a structured array of differences between two points:  e.g. the difference between the closing price of a stock on day T-0 (today) and T-6 (a week ago).  Consequently, if the closing prices are $10.10, $10.20, $10.30, $10.40, and $10.50 (today), then 0/3 is from T-0/T-3 or $10.50 less $10.20 = $0.30.  A…


Added by Don Philip Faithful on August 12, 2017 at 5:30am — No Comments

Why Data Visualization matter now?

Data Visualization is not new, it has been around in various forms for more than thousands of years. 
Ancient Egyptians used symbolic paintings, drawn on walls & pottery, to tell timeless stories of their culture for generations to…

Added by Sandeep Raut on August 12, 2017 at 10:00pm — No Comments

Data Version Control in Analytics DevOps Paradigm

Data Science and DevOps Convergence…


Added by George Vyshnya on August 13, 2017 at 5:30am — No Comments

Dogs vs. Cats: Image Classification with Deep Learning using TensorFlow in Python

The problem

Given a set of labeled images of  cats and dogs, a  machine learning model  is to be learnt and later it is to be used to classify a set of new images as cats or dogs. 

  • The original dataset contains a huge number of images, only a few sample images are chosen (1100 labeled images for cat/dog as training…

Added by Sandipan Dey on August 14, 2017 at 1:00pm — No Comments

Building Convolutional Neural Networks with Tensorflow

In the past year I have also worked with Deep Learning techniques, and I would like to share with you how to make and train a Convolutional Neural Network from scratch, using tensorflow. Later on we can use this knowledge as a building block to make interesting Deep Learning applications.

The contents of this blog-post is as follows:

  1. Tensorflow basics:
    • 1.1 Constants and Variables
    • 1.2 Tensorflow Graphs and Sessions
    • 1.3 Placeholders and…

Added by Ahmet Taspinar on August 15, 2017 at 4:00am — No Comments

Nice Generalization of the K-NN Clustering Algorithm -- Also Useful for Data Reduction

I describe here an interesting and intuitive clustering algorithm (that can be used for data reduction as well) offering several advantages, over traditional classifiers:

  • More robust against outliers and erroneous data
  • Executing much faster
  • Generalizing well known algorithms

You don't need to know K-NN to understand this article -- but click here if you want to…


Added by Vincent Granville on August 15, 2017 at 7:30am — 1 Comment

How to Put AI to Work

Summary:  Whether you are a startup person or data science-minded executive in a larger organization what logic can you apply to spot the most compelling opportunities for AI in your organization.


In 2014 Kevin Kelly, founder of Wired magazine and prolific…


Added by William Vorhies on March 12, 2017 at 9:00am — No Comments

Weekly Digest, August 14

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.

Upcoming Webinars and Resources

Added by Vincent Granville on August 12, 2017 at 1:30pm — No Comments

Data Science Simplified Part 6: Model Selection Methods

In the last article of this series, we had discussed multivariate linear regression model. Fernando creates a model that estimates the price of the car based on five input parameters.…


Added by Pradeep Menon on August 9, 2017 at 4:00pm — 1 Comment

Invest More beyond Tools to Improve Reporting Performance

As a type of front-end data service intended for end-users, reports in applications have received a lot of concerns about their performances.  It’s all users’ wish that parameters in and query and aggregate results out in no time. Though less than twenty seconds’ waiting time is within a tolerant range, three to five minutes will threaten to extend beyond a user’s patience with the worst product experience.

But why is a report so slow? And how shall we optimize its…


Added by HAN Lijun on August 10, 2017 at 12:30am — No Comments

Electronics OEMs Realizing Huge Savings with Data Visualization & Analytics

Introduction to OEMs

The increasing complexity of smart products, more demanding users, and stiff competition are driving the focus of electronics OEMs (original equipment manufacturers) on product quality and productivity. These companies are struggling to improve their operations to increase their production yield, operational efficiency, and product quality. This has been driving demand for  Data Visualization & Analytics solutions over the past few years and as part of their…


Added by Shantanu Chaturvedi on August 10, 2017 at 1:00am — No Comments

Protocol Procedure Complexity In Clinical Trial

Over the past few years, an increasing protocol complexity has garnered a lot of attention among clinical trial experts. It has lead to various important studies beginning from meditating insights metrics warehouse which reveal that clinical studies have reached to a significant level of complexity in the recent times. In spite of a larger increase in metrics in the first half of the past decade and continued warnings from experts, the complexity continues to be on an upward surge through…


Added by Mark on August 10, 2017 at 5:30pm — No Comments

Handbook of Neural Computation 1st Edition, Elsevier,2017

Handbook of Neural Computation explores neural computation applications, ranging from conventional fields of mechanical and civil engineering, to electronics, electrical engineering and computer science. This book covers the numerous applications of artificial and deep neural networks and their uses in learning machines, including image and speech recognition, natural language processing and risk analysis. Edited by renowned authorities in this field,…


Added by Sanjiban Sekhar Roy on August 11, 2017 at 8:00am — No Comments

Two Great Courses on Deep Learning and AI

Deep Learning, Neural Networks and AI

The course is a new one by Andrew Ng, Co-founder, Coursera; Adjunct Professor, Stanford University; formerly head of Baidu AI Group/Google Brain. It will start Aug 15. 

About this course: If you want to break into cutting-edge AI, this course will help you do so. Deep learning engineers are highly…


Added by Vincent Granville on August 10, 2017 at 2:00pm — No Comments

The Rise of the Citizen Data Scientist

The development of Big Data, artificial intelligence and predictive analytics has created extravagant expectations for enterprise productivity growth — and aroused popular anxiety about intelligent information systems taking jobs from human workers. It is ironic, against that backdrop, that…


Added by David Sweenor on August 10, 2017 at 6:24am — No Comments

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