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Weekly Digest, August 21

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

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Added by Vincent Granville on August 18, 2017 at 5:30pm — No Comments

Data Analytics and your Small Business

Acquiring, converting, engaging, and retaining customers is the most important challenge facing businesses of any size. But the proliferation of data, which has been made possible by significant advances in technology, have allowed businesses to capture information on their customers and helped to level the playing field between businesses big and small. Analyzing this data can give you visibility into every facet of your business, helping to inform data-driven and actionable…

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Added by Gavin Graham on August 18, 2017 at 5:00am — No Comments

Top 25 Hadoop Interview Questions Prepared by Experts

1) Compare Hadoop & Spark

                     

Criteria                                           Hadoop                                                   Spark

Dedicated storage                           HDFS                                                     None

Speed of processing                        average                                              …

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Added by Venkatesan M on August 18, 2017 at 12:00am — No Comments

When AI (Artificial Intelligence) Goes Wrong...

The intelligence in AI is computational intelligence, and a better word could be Automated Intelligence. But when it comes to good judgment, AI is not smarter than the human brain that designed it. Many automated systems perform poorly, to the point that you are wondering if AI is an abbreviation for Artificial Innumeracy, 

Critical systems - automated piloting, running a power plant - usually do well with AI and automation, as considerable testing is done before deploying these…

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Added by Vincent Granville on August 17, 2017 at 11:30am — No Comments

Thursday News: ML Automation, Clustering, Regression, Deep Learning, IoT

Here is our list of featured articles and resources posted since Monday:

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Added by Vincent Granville on August 17, 2017 at 7:30am — No Comments

Generative Adversarial Networks (GANs): Engine and Applications


Generative adversarial networks (GANs) are a class of neural networks that are used in unsupervised machine learning. They help to solve such tasks as image generation from descriptions, getting high resolution images from low resolution ones, predicting which drug…

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Added by Luba Belokon on August 17, 2017 at 6:30am — No Comments

Data Lineage: The History of your Data

Data Denialism

A common scenario that data analysts in general encounter is what I like to describe as "data denialism". Often, and especially while consulting, an analyst will find that the data tells a different story than what the customer holds to be true. It is also often the case that, when presenting this finding, the customer will outright deny the evidence, asserting that either the data or the analysis must be wrong. For example, it may be that a retailer focused on the…

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Added by Jesus Ramos on August 16, 2017 at 8:00am — No Comments

Data Science Simplified Part 7: Log-Log Regression Models

In the last few blog posts of this series, we discussed simple linear regression model. We discussed multivariate regression model and methods for selecting the right model.

Fernando has now created a better model.…

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Added by Pradeep Menon on August 16, 2017 at 3:00am — No Comments

Windows Powershell Commands for Beginners

Agenda

  • Introduction of Powershell
  • Need of powershell
  • BackGround of Powershell
  • Tools
  • Why its better than alternatives ?
  • Top Most Administrative Powershell Commands
  • Working with Pipeline
  • Selecting, Sorting, Measuring, Exporting, Importing, Converting,     Filtering, Passing Data in…
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Added by Venkatesan M on August 15, 2017 at 8:30pm — No Comments

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.

 

 …

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Added by William Vorhies on August 15, 2017 at 2:21pm — 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…

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

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…
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Added by Ahmet Taspinar on August 15, 2017 at 4:00am — 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…
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Added by Sandipan Dey on August 14, 2017 at 1:00pm — 2 Comments

The way big data can promote your business ideas

Data is important. It is not a secret for anybody. We can even paraphrase famous saying mentioning that “who owns the data, owns the world”. And if you are a business person, you should know like no one else. Your activity can be changed for better if you use Big Data sources. Sales growth, clever marketing strategy - you can achieve it using Big Data. Let’s check it out what is Big Data and how you can make use of it.

Big Data - meaning and particularities

In fact, Big Data…

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Added by Nataliia Kharchenko on August 14, 2017 at 7:00am — No Comments

Data Version Control in Analytics DevOps Paradigm

Data Science and DevOps Convergence…

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Added by George Vyshnya on August 13, 2017 at 5:30am — 1 Comment

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…
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Added by Sandeep Raut on August 12, 2017 at 10:00pm — 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
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Added by Vincent Granville on August 12, 2017 at 1:30pm — 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…

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Added by Don Philip Faithful on August 12, 2017 at 5:30am — 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…

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Added by Michael Grogan on August 12, 2017 at 5:30am — 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…
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Added by Shreya Gupta on August 11, 2017 at 11:30pm — No Comments

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