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What’s New in Data Prep

Summary:  If you’re still writing code to clean and prep your data you're missing big opportunities for efficiency and consistency with modern data prep platforms.

 

Two things are true. 

  • Data prep still occupies about 80% of our model building time –…
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Added by William Vorhies on September 24, 2018 at 11:00am — No Comments

Weekly Digest, September 24

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.

Announcement

  • Maximize your job prospects. Earn a Penn State Master’s in Data Analytics part-time and online. Learn to design and apply data management techniques…
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Added by Vincent Granville on September 23, 2018 at 8:30am — No Comments

What is the difference between Machine Learning and Artificial Intelligence?

Artificial Intelligence and Machine Learning are two terms related to the world of computer science that can be heard a lot these days. These technologies are helping to bring about a considerable change in different fields today. Be it medical sciences, meteorology, robotics, understanding customer perspectives or scientific developments; these fields are offering an excellent way to move forward without letting technology stagnate.…

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Added by Vijay Singh on September 22, 2018 at 9:00pm — No Comments

Applying Noise Reduction to Stock Market Data

I don’t believe the issue of stock market noise has received much attention from professionals in the investment industry.  I am uncertain if it is much of a topic even among traders.  It certainly wouldn’t be unusual for noise to be discussed among data scientists.  Consider the implications of the suggestion that some trading days provide better guidance than other days – and that analysts should be focused on days that contain less “noise.”  The quality of one’s guidance becomes…

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Added by Don Philip Faithful on September 22, 2018 at 10:18am — No Comments

Free Book: Process Improvement Using Data

This book, initially written for chemical engineers, is actually very interesting for data scientists and machine learning engineers alike. For more free books, visit this page.…

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Added by Capri Granville on September 22, 2018 at 9:30am — No Comments

How do you know if you’re getting value from your data?

Perhaps to no one’s surprise, the growth in companies implementing Big Data and Analytics projects continues to climb – as evidenced by the continued growth in data lakes.  As most companies begin to implement their Big Data and Analytics strategy, they struggle to show value for their efforts.  This can come from several areas:

  • According to…
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Added by Bill Schmarzo on September 22, 2018 at 7:08am — No Comments

Data Science vs AI: Get to the Fundamentals

Introduction: Deriving meaningful information out of heap of data is the minimal requirement for any establishment today for its survival & sustenance. There are many terminologies and buzz words related to this area that blurs the meaning leaving people confused,…

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Added by Niraj Kumar on September 22, 2018 at 5:57am — No Comments

Statistical Significance and p-Values Take Another Blow

I read an article this morning, about a top Cornell food researcher having 13 studies retracted, see here. It prompted me to write this blog. It is about data science charlatans and unethical researchers in the Academia, destroying the value of p-values again, using a well known trick called p-hacking, to get published…

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Added by Vincent Granville on September 21, 2018 at 2:00pm — 2 Comments

Conversational UI is our Future

Conversational user interface (UI) is changing the way that we interact. Intelligent assistants, chatbots and voice-enabled devices, like Amazon Alexa and Google Home, offer a new, natural, and intuitive human-machine interaction and open up a whole new world for us as humans. Chatbots and voicebots ease, speed up, and improve daily tasks. They increase our efficiency and compared to humans, they are also very cost effective…

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Added by Packt Publishing on September 21, 2018 at 1:07am — No Comments

Thursday News: Deep Learning, Stats Book, AI, MLasS Comparison, Feature Selection (Overview)

Here is our selection of featured resources and articles posted this week:

Resources

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Added by Vincent Granville on September 20, 2018 at 11:00am — No Comments

Data Science Glossary

There has been much hype surrounding deep learning and data science learning in recent times, and one of the cornerstones of deep learning is the neural network. In this article, we will look at what a neural network is and get familiar with the relevant terminologies.

In simplest terms, a neural network is an interconnection of neurons. Now the question arises, what is a neuron? To understand neurons in deep learning, we first…

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Added by Divya Singh on September 20, 2018 at 4:00am — No Comments

An overview of feature selection strategies

Introduction

Feature selection and engineering are the most important factors which affect the success of predictive modeling. This remains true even today despite the success of deep learning, which comes with automatic feature engineering. Parsimonious and interpretable models provide simple insights into business problems and therefore they are deemed very valuable. Furthermore, in many occasions the underlying size and structure of the data being analyzed may not allow the use…

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Added by Burak Himmetoglu on September 19, 2018 at 9:58pm — No Comments

Helping Non-Profit Organizations as a Data Scientist

Data Scientists are considered to be highly technical professionals and are typically seen exercising their talent in conventional business industries. However, Data Science is a problem-solving field. Therefore, it can be applied in any field that uses set of data and determines patterns to make decisions. For this reason, Data Scientists have the ability to add value to non-profit organizations.

Big Data and Non-profit Organizations

Like many other business organizations,…

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Added by VAMSI NELLUTLA on September 19, 2018 at 5:00pm — 4 Comments

Free Book: Introduction to Statistics

Online Statistics Education: A Multimedia Course of Study.  Project Leader: David M. Lane, Rice University.

Content:

  • Introduction
  • Graphing Distributions
  • Summarizing Distributions
  • Describing Bivariate Data
  • Probability
  • Research Design
  • Normal Distributions
  • Advanced Graphs
  • Sampling…
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Added by Capri Granville on September 19, 2018 at 1:30pm — No Comments

Introduction to Deep Learning

Guest blog post by Zied HY. Zied is Senior Data Scientist at Capgemini Consulting. He is specialized in building predictive models utilizing both traditional statistical methods (Generalized Linear Models, Mixed Effects Models, Ridge, Lasso, etc.) and modern machine learning techniques (XGBoost, Random Forests, Kernel Methods, neural networks, etc.).…

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Added by Vincent Granville on September 19, 2018 at 1:00pm — 2 Comments

Aggregated Data Dilemma

Okay, I am weird (tell me something that I don’t know, say most of my friends).  For Christmas I wanted a Nike Apple Watch to go with my existing FitBit and Garmin fitness trackers (I look sort of like a cyborg in the photo below…which is always cool). 

While I was intrigued…

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Added by Bill Schmarzo on September 18, 2018 at 9:29am — No Comments

The Fourth Way to Practice Data Science – Purpose Built Analytic Modules

Summary:  Purpose Built Analytic Modules (PBAMs) such as those for Fraud Detection represent a fourth way to practice data science, a new model for the good use of Citizen Data Scientists, and a new market for AI-first companies.

 

It appears that data science has…

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Added by William Vorhies on September 18, 2018 at 9:07am — No Comments

Defining AI Not as Important as Exploiting AI

Today’s Artificial Intelligence (AI) discussions remind me of a Steve Martin skit from the early Saturday Night Live days (1979). In the skit titled “What the Hell is that?”, Steve Martin, later joined by Bill Murray, is looking in the distance at something, repeatedly asking the question “What the hell is that?”  The skit reminds me of today’s AI discussions about “What the hell is AI?”, which distracts from…

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Added by Bill Schmarzo on September 18, 2018 at 4:30am — No Comments

Comparing Machine Learning as a Service: Amazon, Microsoft Azure, Google Cloud AI, IBM Watson

planets

For most businesses, machine learning seems close to rocket science, appearing expensive and talent demanding. And, if you’re aiming at building another Netflix recommendation system, it really is. But the trend of making everything-as-a-service has affected this sophisticated sphere, too. You can jump-start an ML initiative without much investment, which would be the right move if you are new to data science and just want to grab the low hanging fruit.

One of ML's…

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Added by Olexander Kolisnykov on September 18, 2018 at 2:52am — No Comments

Weekly Digest, September 17

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.

Announcement

  • Enterprise AI: Take the Plunge. Data science and advanced analytics front-runner Dataiku announces the release of…
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Added by Vincent Granville on September 16, 2018 at 7:30am — No Comments

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