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smashingmagazine.com June 12, 2018
Building A Pub/Sub Service In-House Using Node.js And Redis

All of them use a similar software architecture at a high level called a “Publish-Subscribe” model, commonly referred to as Pub/Sub. Bored by the definition? Back to our story.
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gengo.ai June 13, 2018
The 50 Best Free Datasets for Machine Learning

What are some open datasets for machine learning? We at Gengo decided to create the ultimate cheat sheet for high quality datasets. These range from the vast (looking at you, Kaggle) or the highly specific (data for self-driving cars).
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947 saves
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medium.com June 14, 2018
Metacat: Making Big Data Discoverable and Meaningful at Netflix

Most large companies have numerous data sources with different data formats and large data volumes. These data stores are accessed and analyzed by many people throughout the enterprise.
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419 saves
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kdnuggets.com June 1, 2018
Data Lake – the evolution of data processing

By Nebojsa Arezina, SmartCat. In recent years, rapid technology advancements have led to a dramatic increase in information traffic. Our mobile networks have increased coverage and data throughput. Landlines are being slowly upgraded from copper to fiber optics.
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80 saves
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oreilly.com June 12, 2018
Microservices, events, and upside-down databases

Download Ben Stopford’s free ebook "Designing Event-Driven Systems" to learn more about microservices, events, and upside-down databases. For as long as we’ve been talking about microservices, we’ve been talking about data.
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298 saves
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dataquest.io June 13, 2018
Python Generators Tutorial

Python generators are a powerful, but misunderstood tool. They're often treated as too difficult a concept for beginning programmers to learn — creating the illusion that beginners should hold off on learning generators until they are ready.
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448 saves
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nautil.us June 14, 2018
We Need to Save Ignorance From AI

After the fall of the Berlin Wall, East German citizens were offered the chance to read the files kept on them by the Stasi, the much-feared Communist-era secret police service. To date, it is estimated that only 10 percent have taken the opportunity.
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185 saves
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techcrunch.com June 13, 2018
Tableau gets AI shot in the arm with Empirical Systems acquisition

When Tableau was founded back in 2003, not many people were thinking about artificial intelligence to drive analytics and visualization, but over the years the world has changed and the company recognized that it needed talent to keep up with new trends.
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259 saves
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kdnuggets.com June 12, 2018
The What, Where and How of Data for Data Science

By Iliya Valchanov, 365 Data Science. Data Science is a term that escapes any single complete definition, which makes it difficult to use, especially if the goal is to use it correctly. Most articles and publications use the term freely, with the assumption that it is universally understood.
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45 saves
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rockhealth.com March 15, 2018
How should the FDA approach the regulation of AI and machine learning in healthcare?

Ground truth is required to train AI/ML models and to demonstrate their effectiveness. When a consensus ground truth dataset isn’t available, it must be collected.
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52 saves

theguardian.com January 19, 2017
How statistics lost their power – and why we should fear what comes next

The ability of statistics to accurately represent the world is declining. In its wake, a new age of big data controlled by private companies is taking over – and putting democracy in peril by In theory, statistics should help settle arguments.
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25,508 saves
engineering.linkedin.com December 16, 2013
The Log: What every software engineer should know about real-time data's unifying abstraction

I joined LinkedIn about six years ago at a particularly interesting time. We were just beginning to run up against the limits of our monolithic, centralized database and needed to start the transition to a portfolio of specialized distributed systems.
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13,518 saves
forbes.com February 12, 2016
Big Data: 33 Brilliant And Free Data Sources Anyone Can Use

Data is ubiquitous — but sometimes it can be hard to see the forest for the trees, as it were. Many companies of various sizes believe they have to collect their own data to see benefits from big data analytics, but it’s simply not true.
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2,057 saves
medium.freecodecamp.org January 20, 2017
The Rise of the Data Engineer

I joined Facebook in 2011 as a business intelligence engineer. By the time I left in 2013, I was a data engineer. I wasn’t promoted or assigned to this new role. Instead, Facebook came to realize that the work we were doing transcended classic business intelligence.
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2,977 saves
fastcodesign.com February 8, 2017
A Dead Simple Tool To Find Out What Facebook Knows About You

That’s the question behind the new Chrome extension Data Selfie.
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13,856 saves
priceonomics.com April 29, 2016
Why That Salesperson Just Won’t Stop Emailing You

This post is adapted from the blog of LeadGenius, a Priceonomics customer. Does your company have interesting data or insights? Become a Priceonomics customer.
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1,322 saves
ft.com March 28, 2014
Big data: are we making a big mistake?

Five years ago, a team of researchers from Google announced a remarkable achievement in one of the world’s top scientific journals, Nature. Without needing the results of a single medical check-up, they were nevertheless able to track the spread of influenza across the US.
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aadrake.com January 18, 2014
Command-line Tools can be 235x Faster than your Hadoop Cluster

Introduction As I was browsing the web and catching up on some sites I visit periodically, I found a cool article from Tom Hayden about using Amazon Elastic Map Reduce (EMR) and mrjob in order to compute some statistics on win/loss ratios for chess games he downloaded from the millionbase archive,
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3,919 saves
datacamp.com January 3, 2017
Python Machine Learning: Scikit-Learn Tutorial

Machine learning is a branch in computer science that studies the design of algorithms that can learn. Typical tasks are concept learning, function learning or “predictive modeling”, clustering and finding predictive patterns.
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849 saves
slack.engineering December 7, 2016
Data Wrangling at Slack

For a company like Slack that strives to be as data-driven as possible, understanding how our users use our product is essential. We knew when we started building this system that we would need flexibility in choosing the tools to process and analyze our data.
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1,923 saves
johnnunemaker.com February 24, 2014
Analytics at GitHub

In the interest of getting back into writing, I want to break the seal with a simple “what have I been up to and thinking about lately” style post. Hopefully future topics will be more focused and frequent. For the past year, I have been working on data and analytics at GitHub.
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1,031 saves
rs.io May 29, 2014
100+ Interesting Data Sets for Statistics

Edit: Hey guys! This has proved to be one of the most popular articles on the site, so I’ve created a supplemental download on the 5 biggest statistics mistakes beginners make and how to avoid them.
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1,651 saves
hbr.org March 6, 2018
Visualizations That Really Work

Knowledge workers need greater visual literacy than they used to, because so much data—and so many ideas—are now presented graphically. But few of us have been taught data-visualization skills.
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3,762 saves
blogs.harvard.edu March 23, 2018
Facebook’s Cambridge Analytica problems are nothing compared to what’s coming for all of online publishing

Let’s start with Facebook’s Surveillance Machine, by Zeynep Tufekci in last Monday’s New York Times. Among other things (all correct), Zeynep explains that “Facebook makes money, in other words, by profiling us and then selling our attention to advertisers, political actors and others.
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code.facebook.com August 31, 2016
Smaller and faster data compression with Zstandard

People are creating, sharing, and storing data at a faster rate than at any other time in history.
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1,386 saves
martinruenz.de February 14, 2016
The dark side of big data

First things first, what is big data about? Control.
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628 saves
multithreaded.stitchfix.com March 16, 2016
Engineers Shouldn’t Write ETL: A Guide to Building a High Functioning Data Science Department

“What is the relationship like between your team and the data scientists?” This is, without a doubt, the question I’m most frequently asked when conducting interviews for data platform engineers.
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2,653 saves
kaushik.net February 25, 2014
7 Data Presentation Tips: Think, Focus, Simplify, Calibrate, Visualize++

There are three elements to our "big data" efforts, or unhyped normal data efforts: Data Collection, Data Reporting, and Data Analysis. We are all aware that the best companies in the world have an optimal DC-DR-DA allocation when it comes to time/money/people: 15%-20%-65%.
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891 saves
techblog.bozho.net November 29, 2017
GDPR – A Practical Guide For Developers

You’ve probably heard about GDPR. The new European data protection regulation that applies practically to everyone. Especially if you are working in a big company, it’s most likely that there’s already a process for getting your systems in compliance with the regulation.
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2,882 saves
analyticsvidhya.com October 26, 2016
17 Ultimate Data Science Projects To Boost Your Knowledge and Skills (& can be accessed freely)

Data science projects offer you a promising way to kick-start your analytics career. Not only you get to learn data science by applying, you also get projects to showcase on your CV. Nowadays, recruiters evaluate a candidate’s potential by his/her work, not as much by certificates and resumes.
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2,100 saves
techblog.netflix.com January 27, 2015
Netflix's Viewing Data: How We Know Where You Are in House of Cards

Over the past 7 years, Netflix streaming has expanded from thousands of members watching occasionally to millions of members watching over two billion hours every month.
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1,269 saves
forbes.com June 16, 2016
Excel Reporting: 5 Reasons Why It Is Bad For Business

We’ve entered the age of big data, in which more and more companies are seeing the value and importance of data in many different areas of their business, from market and customer research, to internal sales figures and HR analytics.
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1,021 saves
forbes.com March 31, 2016
Data Storytelling: The Essential Data Science Skill Everyone Needs

Once your business has started collecting and combining all kinds of data, the next elusive step is to extract value from it.
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1,733 saves
blog.algorithmia.com October 31, 2016
Introduction to Machine Learning for Developers

Today’s developers often hear about leveraging machine learning algorithms in order to build more intelligent applications, but many don’t know where to start.
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3,804 saves
thenextweb.com April 21, 2015
The 14 best data visualization tools

Raw data is boring and it’s difficult to make sense of it in its natural form. Add visualization to it and you get something that everybody can easily digest.
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5,506 saves
econsultancy.com February 26, 2017
17 visualisation tools to make your data beautiful

You don’t need to be a seasoned data scientist or have a degree in graphic design in order to create incredible data visualisations. It has become a lot simpler to mine your data and interpret your insights in an engaging, attractive, and most importantly easy to understand way.
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1,385 saves
nirvacana.com July 8, 2013
Curriculum via Metromap – Pragmatic Perspectives

Data Science, Machine Learning, Big Data Analytics, Cognitive Computing …. well all of us have been avalanched with articles, skills demand info graph’s and point of views on these topics (yawn!). One thing is for sure; you cannot become a data scientist overnight.
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1,562 saves
eng.uber.com July 19, 2016
The Uber Engineering Tech Stack, Part I: The Foundation

Update: This article discusses the lower half of the stack. For the rest, see Part II: The Edge and Beyond. Uber’s mission is transportation as reliable as running water, everywhere, for everyone. To make that possible, we create and work with complex data.
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5,451 saves
idlewords.com
Haunted By Data

In preparing this talk I decided to check out the data landscape, since I hadn't seen it for a while. The terminology around Big Data is surprisingly bucolic. Data flows through streams into the data lake, or else it's captured in logs.
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2,055 saves
stripe.com February 2, 2017
Online migrations at scale

Engineering teams face a common challenge when building software: they eventually need to redesign the data models they use to support clean abstractions and more complex features.
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1,376 saves
adilmoujahid.com August 13, 2016
Interactive Data Visualization of Geospatial Data using D3.js, DC.js, Leaflet.js and Python // Adil Moujahid // Data Analytics and more

The goal of this tutorial is to introduce the steps for building an interactive visualization of geospatial data. To do this, we will use a dataset from a Kaggle competition to build a data visualization that shows the distribution of mobile phone users in China.
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707 saves
johnwittenauer.net December 5, 2014
Machine Learning Exercises In Python, Part 1

This post is part of a series covering the exercises from Andrew Ng's machine learning class on Coursera. The original code, exercise text, and data files for this post are available here. One of the pivotal moments in my professional development this year came when I discovered Coursera.
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2,942 saves
quora.com
How do I become a data scientist?

Strictly speaking, there is no such thing as "data science" (see What is data science? ). See also: Vardi, Science has only two legs: http://portal.acm.org/ft_gateway...
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1,235 saves
confluent.io February 25, 2015
Putting Apache Kafka To Use: A Practical Guide to Building a Streaming Platform (Part 1)

Data systems have mostly focused on the passive storage of data. Phrases like “data warehouse” or “data lake” or even the ubiquitous “data store” all evoke places data goes to sit.
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1,697 saves
medium.freecodecamp.org February 12, 2018
Aspiring data scientist? Master these fundamentals.

Data science is an exciting, fast-moving field to become involved in. There’s no shortage of demand for talented, analytically-minded individuals. Companies of all sizes are hiring data scientists, and the role provides real value across a wide range of industries and applications.
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1,207 saves
medium.com January 8, 2018
A Beginner’s Guide to Data Engineering — Part I

The more experienced I become as a data scientist, the more convinced I am that data engineering is one of the most critical and foundational skills in any data scientist’s toolkit. I find this to be true for both evaluating project or job opportunities and scaling one’s work on the job.
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1,973 saves
techcrunch.com June 23, 2017
Five building blocks of a data-driven culture

How can organizations leverage data as a strategic asset? Data comes at a high price. Businesses must pay for data collection and cleansing, hosting and maintenance, salaries of data engineers, data scientists and analysts, risk of breach and so on. The line items add up.
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3,145 saves
hbr.org June 23, 2017
How to Integrate Data and Analytics into Every Part of Your Organization

Many conversations about data and analytics (D&A) start by focusing on technology. Having the right tools is critically important, but too often executives overlook or underestimate the significance of the people and organizational components required to build a successful D&A function.
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3,273 saves
datasciencecentral.com March 28, 2015
How to Become a Data Scientist - On your own

Big Data, Data Sciences, and Predictive Analytics are the talk of the town and it doesn’t matter which town you are referring to, it’s everywhere, from the White House hiring DJ Patil as the first chief data scientist to the United Nations using predictive analytics to forecast bombings on scho
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1,845 saves
economist.com May 6, 2017
Data is giving rise to a new economy

AN OIL refinery is an industrial cathedral, a place of power, drama and dark recesses: ornate cracking towers its gothic pinnacles, flaring gas its stained glass, the stench of hydrocarbons its heady incense.
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blog.stephenwolfram.com April 24, 2013
Data Science of the Facebook World—Stephen Wolfram Blog

More than a million people have now used our Wolfram|Alpha Personal Analytics for Facebook. And as part of our latest update, in addition to collecting some anonymized statistics, we launched a Data Donor program that allows people to contribute detailed data to us for research purposes.
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3,917 saves
slate.com October 16, 2017
How “Big Data” Went Bust

Five years ago—in February 2012—an article in the New York Times’ Sunday Review heralded the arrival of a new epoch in human affairs: “The Age of Big Data.
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mattturck.com April 5, 2017
Firing on All Cylinders: The 2017 Big Data Landscape

It feels good to be a data geek in 2017. Last year, we asked “Is Big Data Still a Thing?”, observing that since Big Data is largely “plumbing”, it has been subject to enterprise adoption cycles that are much slower than the hype cycle.
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1,374 saves
venturebeat.com July 17, 2016
Forget learning to code: Every employee should know data analysis

“Learn to code.” Around the world, it has been a familiar refrain. And the world has duly learned. Time was that the standard in-school computer education was little more than word processing, spreadsheets and some basic programming.
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3,113 saves
theguardian.com September 26, 2017
I asked Tinder for my data. It sent me 800 pages of my deepest, darkest secrets

The dating app knows me better than I do, but these reams of intimate information are just the tip of the iceberg. What if my data is hacked – or sold? At 9.
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9,296 saves
bigmedium.com June 7, 2017
Design in the Era of the Algorithm

What shall we make? This talk is about what’s coming next for us as designers. What’s the work ahead for us, and what’s our role and responsibility in this future? Designing for what’s next is what my studio Big Medium does.
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1,421 saves
blog.yhat.com January 26, 2017
Becoming a Data Scientist

This blogpost is an excerpt of Springboard's free guide to data science jobs and originally appeared on the Springboard blog. Most data scientists use a combination of skills every day, some of which they have taught themselves on the job or otherwise. They also come from various backgrounds.
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1,082 saves
analyticsvidhya.com February 17, 2017
Top 28 Cheat Sheets for Machine Learning, Data Science, Probability, SQL & Big Data

Data Science is an ever-growing field, there are numerous tools & techniques to remember. It is not possible for anyone to remember all the functions, operations and formulas of each concept. That’s why we have cheat sheets.
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3,803 saves
engineeringblog.yelp.com July 14, 2016
Billions of Messages a Day - Yelp's Real-time Data Pipeline

This is the first post in a series covering Yelp's real-time streaming data infrastructure.
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1,271 saves
medium.freecodecamp.org August 21, 2017
How to become a Data Scientist

Hi! I’m Jose Portilla and I’m an instructor on Udemy with over 250,000 students enrolled across various courses on Python for Data Science and Machine Learning, R Programming for Data Science, Python for Big Data, and many more.
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1,676 saves
forbes.com March 8, 2016
21 Scary Things Big Data Knows About You

What does big data know about you? Quite a lot.
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1,112 saves
research.googleblog.com August 25, 2017
Exploring and Visualizing an Open Global Dataset

To understand visual patterns within the dataset quickly and efficiently, we worked with artist Kyle McDonald to overlay thousands of drawings from around the world. This helped us create composite images and identify trends in each nation, as well across all nations.
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411 saves
medium.com May 24, 2017
How Airbnb Democratizes Data Science With Data University

Data is essential to us at Airbnb. We characterize data as the voice of our users at scale. Thus, data science plays the role of an interpreter — we use data and statistics to understand our users and translate it to a voice that people or machines can understand.
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738 saves
lifehacker.com June 25, 2014
What Is "Big Data," and Who's Collecting It?

Dear Lifehacker, I've been hearing more and more about "big data." What is it, and is it something I should be worried about? Is this another way companies harvest my data and sell it? Dear Bewitched by Buzzwords, "Big data" is the latest tech industry buzz-phrase.
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1,181 saves
kdnuggets.com March 19, 2018
7 Steps to Mastering Data Preparation with Python

Data preparation, cleaning, pre-processing, cleansing, wrangling. Whatever term you choose, they refer to a roughly related set of pre-modeling data activities in the machine learning, data mining, and data science communities. ...
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1,106 saves
mattturck.com February 1, 2016
Is Big Data Still a Thing? (The 2016 Big Data Landscape)

In a tech startup industry that loves its shiny new objects, the term “Big Data” is in the unenviable position of sounding increasingly “3 years ago”. While Hadoop was created in 2006, interest in the concept of “Big Data” reached fever pitch sometime between 2011 and 2014.
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1,209 saves
datasciencecentral.com February 27, 2017
Data Science, Machine Learning, BI Explained in a Amazing Few Pictures

Guest blog post by Rubens Zimbres, PhD. This article brings images from my work modeling with Mathematica, my experience as a Business Analyst and also my doctorate lessons.
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1,789 saves
alyssafrazee.com January 2, 2014
alyssa frazee

My sister is a senior undergraduate majoring in sociology. She just landed an awesome analyst job for next semester and was told she'll be using some R in the course of her work.
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924 saves
blog.codeclimate.com
5 Reasons to Use Protocol Buffers Instead of JSON For Your Next Service

Service-Oriented Architecture has a well-deserved reputation amongst Ruby and Rails developers as a solid approach to easing painful growth by extracting concerns from large applications. These new, smaller services typically still use Rails or Sinatra, and use JSON to communicate over HTTP.
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2,133 saves
medium.com June 20, 2015
Doing Data Science at Twitter

On June 17, 2015, I celebrated my two year #Twitterversary @Twitter. Looking back, the Data Science (short for DS) landscape at Twitter has shifted quite a bit:
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3,114 saves
forbes.com March 14, 2016
Top 10 Hot Big Data Technologies

As the big data analytics market rapidly expands to include mainstream customers, which technologies are most in demand and promise the most growth potential? The answers can be found in TechRadar: Big Data, Q1 2016, a new Forrester Research report evaluating the maturi
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1,050 saves
archagon.net March 24, 2018
Data Laced with History: Causal Trees & Operational CRDTs

(Sorry about the length! At some point in the distant past, this was supposed to be a short blog post. If you like, you can skip straight to the demo section which will get to the point faster than anything else.)
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447 saves
lifehacker.com October 25, 2016
How to Lie to Yourself and Others With Statistics

Misusing statistics is one of the most powerful ways to lie. Normally, we teach you how to avoid misinterpreting statistics, but knowing how numbers are manipulated can help you spot when it happens.
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3,191 saves
forbes.com May 28, 2013
A Very Short History Of Data Science

The story of how data scientists became sexy is mostly the story of the coupling of the mature discipline of statistics with a very young one–computer science.
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1,476 saves
medium.com February 15, 2016
Evolution of the Netflix Data Pipeline

Our new Keystone data pipeline went live in December of 2015. In this article, we talk about the evolution of Netflix’s data pipeline over the years. This is the first of a series of articles about the new Keystone data pipeline. Netflix is a data-driven company.
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1,544 saves
mckinsey.com January 25, 2017
Making data analytics work for you—instead of the other way around

Does your data have a purpose? If not, you’re spinning your wheels. Here’s how to discover one and then translate it into action.
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2,112 saves
huffingtonpost.com September 28, 2017
The 9 Best Free Online Big Data And Data Science Courses

Demand for skilled data scientists continues to be sky-high, with IBM recently predicting that there will be a 28% increase in the number of employed data scientists in the next two years.
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924 saves
code.facebook.com November 14, 2014
Introducing data center fabric, the next-generation Facebook data center network

The more than 1.35 billion people who use Facebook on an ongoing basis rely on a seamless, “always on” site performance.
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1,755 saves
segment.com November 20, 2015
Our Engineering Team's Best Practices

Every month, Segment collects, transforms and routes over 50 billion API calls to hundreds of different business-critical applications. We’ve come a long way from the early days, where my co-founders and I were running just a handful of instances.
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480 saves
fastcompany.com September 26, 2017
Even This Data Guru Is Creeped Out By What Anonymous Location Data Reveals About Us

When Edward Snowden blew the lid off of the NSA’s mass surveillance program, he also revealed the extent of the government’s smartphone location tracking records.
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13,960 saves
hackernoon.com November 14, 2016
Aspiring Data Scientists! Learn the basics with these 7 books!

In the last few years I spent a significant time with reading books about Data Science. I found these 7 books the best. These together are a very valuable source of learning the basics. It drives you through everything, you need to know.
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2,467 saves
hbr.org March 16, 2017
A 5-Step Process to Get More Out of Your Organization’s Data

Daniel (not his real name) was a VP human resource manager at a Fortune 500 company. I asked him whether he had collected any data that could provide him with insights into systematic patterns. “I made sure we get exit interviews done with every single employee who is leaving us,” he replied.
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762 saves
auth0.com November 9, 2015
Intro to Microservices, Part 4: Dependencies and Data Sharing

In this post in the microservices series we will study how to manage inter-service dependencies and how to deal with implicit interfaces in the form of data sharing. We will also extend our existing examples from the microservices series to show some of the concepts in this post.
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368 saves
segment.com May 17, 2017
Spotting a Million Dollars in Your AWS Account

Recently we shared the techniques we used to save more than a million dollars annually on our AWS bill.
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967 saves
thenewinquiry.com October 9, 2014
View From Nowhere

On the cultural ideology of Big Data. “What science becomes in any historical era depends on what we make of it” —Sandra Harding, Whose Science? Whose Knowledge? (1991)
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1,108 saves
medium.freecodecamp.org January 25, 2017
I ranked every Intro to Data Science course on the internet, based on thousands of data points

A year ago, I dropped out of one of the best computer science programs in Canada. I started creating my own data science master’s program using online resources. I realized that I could learn everything I needed through edX, Coursera, and Udacity instead.
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2,367 saves
minimaxir.com October 2, 2015
How to Analyze Every Reddit Submission and Comment, in Seconds, for Free

While working on my statistical analysis of 142 million Reddit submissions last year, I had a surprising amount of trouble settings things up. It took a few hours to download the 40+ gigabytes of compressed data, and another few hours to parse the data and store in a local database.
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506 saves
blog.insightdatascience.com October 3, 2017
What would be useful for aspiring data scientists to know?

Eric Ma has a PhD in Biological Engineering from MIT, and was an Insight Health Data Fellow in Summer 2017. Eric has since joined the Scientific Data Analysis team at Novartis, where he gets to pursue his dream role of doing data science in the context of the life sciences.
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421 saves
economist.com August 13, 2015
We’ll see you, anon

FREQUENT visitors to the Hustler Club, a gentlemen’s entertainment venue in New York, could not have known that they would become part of a debate about anonymity in the era of “big data”.
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1,042 saves
blog.districtdatalabs.com December 29, 2016
Data Exploration with Python, Part 1

Exploratory data analysis (EDA) is an important pillar of data science, a critical step required to complete every project regardless of the domain or the type of data you are working with.
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504 saves
blog.bigml.com February 28, 2013
Data, Data, Data: Thousands of Public Data Sources

We love data, big and small and we are always on the lookout for interesting datasets. Over the last two years, the BigML team has compiled a long list of sources of data that anyone can use.
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663 saves
towardsdatascience.com November 13, 2017
Diary of a Data Scientist at Booking.com

I joined Booking.com as a data scientist about two and a half years back, straight after a 3 years consulting gig in Dubai. Moving from consulting to a pure data science role was a big shift in my career and in hindsight I’m very happy I made that choice.
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780 saves
washingtonpost.com December 13, 2016
Scientists are frantically copying U.S. climate data, fearing it might vanish under Trump

Alarmed that decades of crucial climate measurements could vanish under a hostile Trump administration, scientists have begun a feverish attempt to copy reams of government data onto independent servers in hopes of safeguarding it from any political interference.
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6,683 saves
kdnuggets.com April 3, 2018
Every Intro to Data Science Course on the Internet, Ranked

A year ago, I dropped out of one of the best computer science programs in Canada. I started creating my own data science master’s program using online resources. I realized that I could learn everything I needed through edX, Coursera, and Udacity instead.
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1,017 saves
venturebeat.com April 1, 2014
Data scientists need their own GitHub. Here are four of the best options

Imagine if a company’s three highly valued data scientists can happily work together without duplicating each other’s efforts and can easily call up the ingredients and results of each other’s previous work. That day has come.
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769 saves
thinkgrowth.org March 31, 2017
The Startup Founder’s Guide to Analytics

You need analytics. I’m very confident of that, because today, everyone needs analytics. Not just product, not just marketing, not just finance… sales, fulfillment, everyone at a startup needs analytics today.
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2,538 saves