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July 2019 Blog Posts (105)

Scaling Innovation:  Whiteboards versus Maps

I love watching the NBA’s Golden State Warriors play basketball. Their offensive “improvisation” is a thing of beauty in their constant ball movement in order to find the “best” shot. They are a well-oiled machine optimizing split-second decisions in an ever-changing landscape that is heavily influenced by questions such as:

  • Who is my defender?
  • What are the strengths of my defender?
  • From where is help likely to come if I make a move to the basket?
  • Who…
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Added by Bill Schmarzo on July 5, 2019 at 12:51pm — No Comments

Data Science Central Monday Digest, July 8

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. To subscribe, follow this link.  

Featured Resources and Technical…

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Added by Vincent Granville on July 5, 2019 at 7:00am — No Comments

Top 8 Data Science Use Cases in Construction

Introduction

With every article, we keep proving that data science has found broad application in numerous business areas. Now, the turn came to the construction industry as well. The world is overloaded with data. It results in a steady improvement in…

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Added by Igor Bobriakov on July 5, 2019 at 5:00am — No Comments

Top 10 Data Science Use Cases in Energy and Utilities

The energy sector is under constant development, and more of significant inventions and innovations are yet to come. The energy use has always been involved in other industries like agriculture, manufacturing, transportation, and many others. Thus these industries tend to enlarge…

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Added by Igor Bobriakov on July 4, 2019 at 10:00pm — 1 Comment

Univariate Analysis – A Key to the Mystery Behind Data!

Exploratory Data Analysis or EDA is that stage of Data Handling where the Data is intensely studied and the myriad limits are explored. EDA literally helps to unfold the mystery behind such data which might not make sense at first glance. However, with detailed analysis, we can use the same data to provide miraculous results which can help boost large scale business decisions with excellent accuracy. This not only helps business conglomerations to evade likely pitfalls in the future but also…

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Added by Divya Singh on July 4, 2019 at 7:30pm — No Comments

How Retailers Use Artificial Intelligence to Innovate Customer Experience and Enhance Operations

Digitalization influences how businesses operate and build and maintain relationships with customers. With the internet open 24/7, consumers can save time and shop online at their convenience. In 2017, global eCommerce sales accounted for 10.2 percent of all retail sales ($2.3 trillion US). This figure is projected to reach 17.5 percent in 2021. Revenue from eCommerce sales is expected to grow to $4.88 trillion US.…

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Added by Kateryna Lytvynova on July 4, 2019 at 6:00am — No Comments

The Math of Decision Trees, Random Forest and Feature Importance in Scikit-learn and Spark

This article was written by Stacey Ronaghan.

Introduction

This post attempts to consolidate information on tree algorithms and their implementations in…

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Added by Andrea Manero-Bastin on July 4, 2019 at 5:00am — No Comments

How to build your own Neural Network from scratch in Python

This article was written by James Loy.

 

Update: When I wrote this article a year ago, I did not expect it to be thispopular. Since then, this article has been viewed more than 450,000 times, with more than 30,000 claps. It has also made it to the front page of Google, and it is among the first few search results for…

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Added by Andrea Manero-Bastin on July 4, 2019 at 4:30am — No Comments

Data Quality Case Studies: How We Saved Clients Real Money Thanks to Data Validation

Machine learning models grow more powerful every week, but the earliest models and the most recent state-of-the-art models share the exact same dependency: data quality. The maxim “garbage in – garbage out” coined decades ago, continues to apply today. Recent examples of data verification shortcomings abound, including JP Morgan/Chase’s 2013 fiasco and this lovely…

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Added by Michał Frącek on July 4, 2019 at 4:21am — No Comments

Lightweight but effective way of documenting a group of Jupyter Notebooks

My app Qubiter has a folder full of Jupyter notebooks (27 of them, in fact). Opening a notebook takes a short while, which is slightly annoying. I wanted to give Qubiter users the ability to peek inside all the notebooks at once, without having to open all of them. Qubiter’s new SUMMARY.ipynb notebook allows the user to do just that.

SUMMARY.ipynb scans the directory in which it lives to find all Jupyter notebooks (other than itself) in that directory. It then prints for every…

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Added by Robert R. Tucci on July 4, 2019 at 3:08am — No Comments

How the Mathematics of Fractals Can Help Predict Stock Markets Shifts

In financial markets, two of the most common trading strategies used by investors are the momentum and mean reversion strategies. If a stock exhibits momentum…

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Added by Marco Tavora on July 4, 2019 at 12:30am — 3 Comments

Data Science Central Thursday Digest, July 4

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

Technical resources 

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Added by Vincent Granville on July 3, 2019 at 7:30pm — No Comments

New Book: Data Science for Healthcare - Methodologies and Applications

This Springer book seeks to promote the exploitation of data science in healthcare systems. The focus is on advancing the automated analytical methods used to extract new knowledge from data for healthcare applications. To do so, the book draws on several interrelated disciplines, including machine learning, big data analytics, statistics, pattern recognition, computer vision, and Semantic Web technologies, and focuses on their direct application to…

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Added by Sergio Consoli on July 3, 2019 at 5:45am — No Comments

Exploratory Data Analysis with Python

In addition to being the sexiest job of the twenty-first century, Data Science is new electricity as quoted by Andrew Ng. A lot of professionals from various disciplines and domain are looking to make a transition into the field of analytics and use Data Science to solve various problems across multiple channels. Being an inter-disciplinary study, one could easily mine data for various operations and help decision-makers make relevant conclusions to achieve…

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Added by Divya Singh on July 2, 2019 at 8:00pm — No Comments

Writing/Reading Large R dataframes/data.tables -- Addendum.



After posting my most recent blog using …

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Added by steve miller on July 2, 2019 at 9:00am — No Comments

How To Choose An NLP Vendor For Your Organization

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Added by Shaily Baheti on July 2, 2019 at 12:30am — No Comments

How Long Does It Take to Learn Python for Data Science?

Python is the most loved, dreaded, and wanted programming languages by most developers, according to StackOverflow survey.  Popular among most professional software developers, Python was ranked the world’s seventh popular programming language.

A study by PYPL Popularity of Programming Language Index (a study that monitors the frequency of searches regarding the popular programming languages to learn) predicted that it showed that there was a growth of 17.1% during the last…

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Added by Yoey Thamas on July 2, 2019 at 12:29am — No Comments

Open-source Logistic Regression FPGA core for accelerated Machine Learning

Machine learning algorithms are extremely computationally intensive and time consuming when they must be trained on large amounts of data. Typical processors are not optimized for machine learning applications and therefore offer limited performance. Therefore, both academia an industry is focused on the development of specialized architectures for the efficient acceleration of machine learning applications.

FPGAs are programmable chips that can be configured with tailored-made…

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Added by Chris Kachris on July 1, 2019 at 10:00pm — No Comments

Critical skills set to make or break a data scientist

 A data scientist must know how to approach the extent of any problem; it means identifying features and figuring out the question that how to frame the desired answer is the key to become the most wanted data scientist. …

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Added by Nisha Dhiman on July 1, 2019 at 9:00pm — No Comments

How Data Science is Playing a Big Role in Higher Education?



Data science is a growing and promising discipline that has impacted various domains, including higher education. Owing to its ability to use precise methods and platforms to extract insights from data, several academic institutions are incorporating data science into their operations and educational curriculum. This helps them engage students, improve educational…

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Added by Gaurav Belani on July 1, 2019 at 8:30pm — No Comments

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