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All Blog Posts Tagged 'machine' (232)

Understanding Machine Learning: How machines learn?

“If (there) was one thing all people took for granted, (it) was conviction that if you feed honest figures into a computer, honest figures (will) come out. Never doubted it myself till I met a computer with a sense of humor.”

― Robert A. Heinlein, The Moon is a Harsh Mistress

 

This post is the first in a series of articles in which we will explain what Machine Learning is. You don’t have to have formal training or…

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Added by Algolytics on April 13, 2017 at 4:00am — 3 Comments

Feature Engineering with Tidyverse

In this blog post, I will discuss feature engineering using the Tidyverse collection of libraries. Feature engineering is crucial for a variety of reasons, and it requires some care to produce any useful outcome. In this post, I will consider a dataset that contains description of crimes in San Francisco between…

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Added by Burak Himmetoglu on April 10, 2017 at 7:30am — No Comments

History as a guide to IoT growth trajectory

Internet of Things (IoT) has generated a ton of excitement and furious activity. However, I sense some discomfort and even dread in the IoT ecosystem about the future – typical when a field is not growing at a hockey-stick pace . . .

“History may not repeat itself but it rhymes”, Mark Twain may have said. What history does IoT rhyme with?

 I have often used this diagram to crisply define IoT.…

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Added by PG Madhavan on April 2, 2017 at 1:00pm — 1 Comment

Finding "Gems" in Big Data

(Photo credit:  Rob Lavinsky, iRocks.com – CC-BY-SA-3.0)

In 1945, Count ,Richard Taaffe* a Dublin gem collector, was sorting through a set of spinel gems that he had bought, and found one…

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Added by Peter Bruce on March 30, 2017 at 2:30pm — No Comments

Walk-through Of Patient No-show Supervised Machine Learning Classification With XGBoost In R

Overview

This is a project I've been working on for some time to help improve the missed opportunity rate (no-show rate) at all medical centers. It demonstrates how to extract datasets from an SQL server and load them directly into an R environment. It also demonstrates the entire machine learning process, from engineering new features, tuning and training the model, and finally measuring the model's performance. I would like to share my results and methodology as a guide to help…

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Added by James Marquez, MBA, PMP on March 21, 2017 at 8:30am — No Comments

Difference of Data Science, Machine Learning and Data Mining

Data is almost everywhere. The amount of digital data that currently exists is now growing at a rapid pace. The number is doubling every two years and it is completely transforming our basic mode of existence. According to a paper from IBM, about 2.5 billion gigabytes of data had been generated on a daily basis in the year 2012. Another article from Forbes informs us…

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Added by Leonard Heiler on March 20, 2017 at 10:30am — 2 Comments

What makes a great data scientist?

A data scientist is an umbrella term that describes people whose main responsibility is leveraging data to help other people (or machines) making more informed decisions. The spectrum of data scientist roles is so broad that I will keep this discussion for my next post. What I really want to focus is on what are the distinctive characteristics of a great data scientist.

Over the years that I have worked with data and analytics I have found that this has almost nothing to do with…

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Added by Karolis Urbonas on March 20, 2017 at 12:00am — No Comments

Numerous reasons why Digital Transformation fails

Many organizations today have realized that digital transformation is essential to their success.

But many of them forget that focus of a digital transformation is not digitization or even technology, it is the Customer!

Digital Transformation is not easy or small endeavor for any business. Several levers will need to be turned in unison just to ensure…

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Added by Sandeep Raut on March 18, 2017 at 5:30am — No Comments

Linear, Machine Learning and Probabilistic Approaches for Time Series Analysis

In this post, we consider different approaches for time series modeling. The forecasting approaches using linear models, ARIMA alpgorithm, XGBoost machine learning algorithm are described. Results of different model combinations are shown. For probabilistic modeling the approaches using copulas and Bayesian inference are considered.

INTRODUCTION

Time series analysis, especially forecasting, is an important problem of modern…

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Added by Bohdan Pavlyshenko on February 26, 2017 at 5:30am — 2 Comments

Ali Baba's magic - Open Sesame and Digital Transformation

Do you still remember our childhood story of Ali Baba and 40 thieves?



“Open Sesame” was the magical phrase that a poor woodcutter Ali Baba uttered, to open the door of a secret cave in which 40 thieves had hidden bags of gold and treasure. The power of his voice, and using the right words, gave him access to that fortune, and changed his life forever.



We are in the same cusp of open sesame to Digital Transformation and changing our lives. It’s a fact that our lives are… Continue

Added by Sandeep Raut on January 28, 2017 at 12:46pm — No Comments

Using ML-driven marketing optimization to solve the attribution conundrum

Accurate multichannel campaign attribution has stumped the online marketing industry for years. But what if the solution is to stop worrying about attribution, and move to an optimization-driven approach?

You know those photo mosaic images, which suddenly became terribly popular a few years back? They cleverly use lots of individual tiny images to make up one large image. If you look closely you can make out the…

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Added by Ian Thomas on January 27, 2017 at 9:30am — No Comments

See this simple introduction to Natural Language Processing (NLP)

Today, with of Digitization  everything, 80 percent the data being created is unstructured. 
Audio, Video, our social footprints, the data generated from conversations between customer service reps, tons of legal document’s texts processed in financial sectors are examples of unstructured data stored in Big Data.
Organizations are turning to natural…
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Added by Sandeep Raut on January 21, 2017 at 10:00am — No Comments

Can computers think? An epistemology for Artificial Intelligence

As AI enters our homes through smart home devices or tries to conquer our streets through self-driving cars, one need not be a Luddite to contemplate the potentially heavy implications of AI upon our daily lives and livelihood. The key to answering the question and indeed to understand the ultimate limits of AI is to ask if machines can really think. In this article, I list three tests drawn from three different disciplines to address that…

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Added by Srividya Kannan Ramachandran on January 20, 2017 at 12:02pm — No Comments

Charting a Mandate for a Chief Data Scientist

The profusion of big data alongside helpful nudges from Wall Street has inspired many companies to create Chief Data Officer(CDO) and Chief Data Scientist(CDS) roles. The mandate for these roles remains inchoate much in tune with the incipient nature of application of machine learning and predictive analytics within a large corporate structure.

In a previous post, I had introduced a new paradigm – the…

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Added by Srividya Kannan Ramachandran on January 4, 2017 at 6:00pm — No Comments

Could Machine Learning Help Cathay Pacific Save Millions From Travel Delays?



NB: Cathay Pacific

Aircraft fuel is without a doubt the biggest cost for any airline and often receives widespread attention, especially when airlines hedge their bets the wrong way. Cathay Pacific reported a HK$4.49…

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Added by Mark Ross-Smith on December 27, 2016 at 8:30am — 1 Comment

Deciphering the Neural Language Model

Recently, I have been working on the Neural Networks for Machine Learning course offered by Coursera and taught by Geoffrey Hinton. Overall, it is a nice course and provides an introduction to some of the modern topics in deep learning. However, there are instances where the student has to do lots of extra work in order to understand the topics covered in full detail.

One of the assignments in…

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Added by Burak Himmetoglu on December 17, 2016 at 10:00am — No Comments

Want to know how to choose Machine Learning algorithm?

Machine Learning is the foundation for today’s insights on customer, products, costs and revenues which learns from the data provided to its algorithms.
Some of the most common examples of machine learning are Netflix’s algorithms to give movie suggestions based on movies you have watched in the past or Amazon’s algorithms that recommend products…
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Added by Sandeep Raut on December 16, 2016 at 3:30pm — 4 Comments

Correlation does not imply causation

A popular phrase tossed around when we talk about statistical data is “there is correlation between variables”. However, many people wrongly consider this to be the equivalent of “there is causation between variables”. It’s important to explain the distinction: Correlation means that once we know how one variable changes we can make reasonable deductions about how other variables change There are several variants of correlation:

1. Positive…

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Added by Algolytics on December 13, 2016 at 4:30am — 1 Comment

Q&A: The Transformative Power of Big Data Paired with Data Science

Data analytics is a mature discipline at this point, and even those outside the data science world generally understand what it’s all about. Modern data science, however, is still new enough to spur questions. Vincent Glanville, Executive Data Scientist at Data Science Central, spoke with Roy Wilds, Chief Data Scientist from PHEMI, a Vancouver-based big data startup, about the best way to educate people…

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Added by Roy Wilds, PhD, PHEMI Systems on December 6, 2016 at 8:00am — No Comments

Machine learning as a service ? Might lose sleep over this !

    This post is 'not' intended to teach people how to use popular predictive modelling APIs for free. Although, to your surprise, this isn't a far fetched possibility. Trained Machine learning models are basically a function that maps feature vectors to the output variable. Upon querying with a test instance, the model predicts an outcome, assigning…

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Added by Ashish kumar on November 28, 2016 at 5:00pm — No Comments

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