Dataconomy
FEBRUARY 26, 2019
After retailers suffered a bad year with bankruptcies, store closures and lower store footfall, we discuss why now is the time for retailers to invest in data and advanced technologies to boost consumer relations. Bricks and mortar retailers would sooner forget 2018. The year that brought 16 U.S. bankruptcies, The post How machine learning can drive retail success appeared first on Dataconomy.
Eugene Yan
FEBRUARY 1, 2019
Taking the best from agile and modifying it to fit the data science process (Part 2 of 2).
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Data Science 101
FEBRUARY 11, 2019
The profile of a data scientist is changing slightly as the profession becomes more solidified. Data Science 365 conducts a study to determine some of the characteristics of a “typical data scientist.” The below infographic covers a wealth of information from programming languages used to educational backgrounds to locations. It is definitely worth looking at to understand the attributes of a data scientist in 2019.
DataRobot
FEBRUARY 26, 2019
DataRobot , the leader in automated machine learning, is proud to announce its acquisition of Cursor , a San Francisco-based company that provides a data collaboration platform which helps organizations find, understand and use data more efficiently.
Speaker: Tamara Fingerlin, Developer Advocate
Apache Airflow® 3.0, the most anticipated Airflow release yet, officially launched this April. As the de facto standard for data orchestration, Airflow is trusted by over 77,000 organizations to power everything from advanced analytics to production AI and MLOps. With the 3.0 release, the top-requested features from the community were delivered, including a revamped UI for easier navigation, stronger security, and greater flexibility to run tasks anywhere at any time.
DataRobot Blog
FEBRUARY 10, 2019
by Jen Underwood. In the spirit of Valentine’s Day, let’s explore a fun little Relationship App quiz that forecasts how long your relationship will last. Data from a Stanford University study, How Couples. Read More.
Victor Zhou
FEBRUARY 22, 2019
I usually check the weather on my phone, but last week I visited weather.com on my laptop. Here’s what I saw: This was taken with Network throttling set to "Fast 3G" in Chrome to simulate the slow connection I had. Why is the image in the top right so much slower to load than the others around it? I opened up Chrome Devtools to check it out: “intrinsic: 1280 x 720 pixels”.
Data Science Current brings together the best content for data science professionals from the widest variety of thought leaders.
ML Review
FEBRUARY 11, 2019
Understanding building blocks of ULMFIT Last week I had the time to tackle a Kaggle NLP competition: Quora Insincere Questions Classification. As it’s easy to understand from the name, the task is to identify sincere and insincere questions given the question text. In short it’s a binary classification problem. I recently completed Fast.ai Part 1 (2019).
Data Science 101
FEBRUARY 28, 2019
Data Journalism Handbook 2 – Online beta access to the first 21 chapters Select Star SQL – A book that is also a walk-through interactive tutorial for learning SQL Dive Into Deep Learning – A very detailed and up-to-date book on Deep Learning; used at Berkeley. It also includes Jupyter notebooks. R for Data Science – Just like the title says, learn to use R for data science.
DataRobot
FEBRUARY 21, 2019
This blog is meant to be a fun and unique take on predicting Best Picture for the 91st Academy Awards.
Depends on the Definition
FEBRUARY 11, 2019
This time we have a look into the magnitude library, a feature-packed Python package and vector storage file format for utilizing vector embeddings in machine learning models in a fast, efficient, and simple manner developed by Plasticity.
Speaker: Alex Salazar, CEO & Co-Founder @ Arcade | Nate Barbettini, Founding Engineer @ Arcade | Tony Karrer, Founder & CTO @ Aggregage
There’s a lot of noise surrounding the ability of AI agents to connect to your tools, systems and data. But building an AI application into a reliable, secure workflow agent isn’t as simple as plugging in an API. As an engineering leader, it can be challenging to make sense of this evolving landscape, but agent tooling provides such high value that it’s critical we figure out how to move forward.
Christian Haschek
FEBRUARY 8, 2019
Disclaimer: This article is the result of a few weeks of research.
Dataconomy
FEBRUARY 6, 2019
Big Data and AI can help with the growing care provider shortage. Here is how and why. One percent of the global population possesses 40-percent of all the world’s wealth, a persistent issue for which economists and politicians have debated about for some time. Economic inequality is a problem that’s. The post Can Big Data Help Provide Affordable Healthcare?
Explosion
FEBRUARY 5, 2019
In this video, Ines talks about a few frequently asked questions and shares some general tips and tricks for how to structure your NLP annotation projects, how to design your label schemes and how to solve common problems.
Data Science 101
FEBRUARY 13, 2019
The field of data science is moving fast. People are claiming to be data scientists; yet the knowledge, experience, and backgrounds of those people can be very different. Different is not bad. However, there a little standards around what exactly a data scientist is. Sticking with this week’s theme of “What is a Data Scientist”, an organization titled, Initiative for Analytics and Data Science Standards (IADSS) has kicked-off a research study at global scale.
Speaker: Andrew Skoog, Founder of MachinistX & President of Hexis Representatives
Manufacturing is evolving, and the right technology can empower—not replace—your workforce. Smart automation and AI-driven software are revolutionizing decision-making, optimizing processes, and improving efficiency. But how do you implement these tools with confidence and ensure they complement human expertise rather than override it? Join industry expert Andrew Skoog as he explores how manufacturers can leverage automation to enhance operations, streamline workflows, and make smarter, data-dri
DataRobot
FEBRUARY 27, 2019
Implementing machine learning models into analytics tools used to be time-consuming and technically challenging. With the DataRobot and Qlik partnership , this is no longer the case. The Qlik2DataRobot client and server-side extensions ensure that enterprises of all sizes can now get insights in less time, giving business users the power of automated machine learning decision-making within any analytics workflow.
Victor Zhou
FEBRUARY 15, 2019
Back in early 2016, I began building a web game called GeoArena. Looking back, my biggest regret is not using Webpack from the beginning. When I started GeoArena, I was very new to web development. Having never heard of module bundlers before, I instead homebrewed my own approaches for serving Javascript on the web. This post explores the problems with those methods and explains why you should be using Webpack instead.
DataCentric podcast
FEBRUARY 8, 2019
This year is shaping up to be a huge year for IT and enterprise datacenter architecture. Matt and Steve talk about what they see as the big trends in 2019 that are most impactful, as well as some anti-trends. It's an insightful 28 minutes! 00:46 News: CES, IBM Quantum Computing, & Huawei builds a server ARM part 03:20 Trend: ARM in the DataCenter?
Dataconomy
FEBRUARY 21, 2019
The era of everything-as-a-service (XaaS) has provided both an opportunity and a challenge for companies across industries. The XaaS model, a subscription-based solution that makes cloud-based applications available on demand unlike the traditional license-based platforms of the past, delivers several noteworthy advantages over its predecessors. Between cost reductions and easier.
Speaker: Frank Taliano
Documents are the backbone of enterprise operations, but they are also a common source of inefficiency. From buried insights to manual handoffs, document-based workflows can quietly stall decision-making and drain resources. For large, complex organizations, legacy systems and siloed processes create friction that AI is uniquely positioned to resolve.
Dataconomy
FEBRUARY 19, 2019
In 2018, the GDPR changed how tech companies handle data privacy. In 2019, it’s influencing the public’s perception of internet privacy and changing how tech companies treat violations—and one another. Last month, I wrote about the state of internet privacy in the context of the GDPR and other regulations that. The post Apple’s privacy play keeps internet regulators at bay appeared first on Dataconomy.
DataRobot
FEBRUARY 19, 2019
You’ve decided: DataRobot is cool. You saw a demo. Your people tell you they like it. You like the way it makes data scientists more productive. And you love the way it helps you introduce new people to machine learning.
DataRobot
FEBRUARY 18, 2019
In order t o further help you accelerate AI success with the team and tools you have in place, we are pleased to share our new DataRobot What-If extension for Tableau. The DataRobot What-If extension empowers you to analyze the cause-and-effect of different variables on a predicted outcome within a familiar Tableau experience. With the DataRobot What-If extension, you can make better informed, more actionable decisions to optimize outcomes.
DataRobot
FEBRUARY 25, 2019
Liverpool Victoria (LV=) is one of the United Kingdom’s largest insurance companies with over five million customers. LV= offers a wide range of products, such as car, home, pet, travel, and life insurance. Pardeep Bassi, the Head of Data Science at LV=, spoke at our AI Experience London event about “Driving the Implementation of Machine Learning Across a Business.”.
Speaker: Chris Townsend, VP of Product Marketing, Wellspring
Over the past decade, companies have embraced innovation with enthusiasm—Chief Innovation Officers have been hired, and in-house incubators, accelerators, and co-creation labs have been launched. CEOs have spoken with passion about “making everyone an innovator” and the need “to disrupt our own business.” But after years of experimentation, senior leaders are asking: Is this still just an experiment, or are we in it for the long haul?
Victor Zhou
FEBRUARY 9, 2019
Here’s a bit of Javascript that prints “Hello World!” on two lines: ( function ( ) { ( function ( ) { console. log ( 'Hello' ) } ) ( ) ( function ( ) { console. log ( 'World!' ) } ) ( ) } ) ( ) …except it fails with a runtime error. Can you spot the bug without running the code? Scroll down for a hint. Hint Here’s the text of the error: TypeError: (intermediate value)(.) is not a function What’s going on?
DataRobot
FEBRUARY 28, 2019
A recently published research paper from Columbia University described a common dilemma in machine learning. Back in the mid-1990s, one cost-effective healthcare initiative investigated the application of machine learning to predict the probability of death for patients with pneumonia so that high-risk patients could be admitted to the hospital while low-risk patients were treated as outpatients.
Victor Zhou
FEBRUARY 4, 2019
A few months ago, I needed a way to detect profanity in user-submitted text strings: This shouldn’t be that hard, right? I ended up building and releasing my own library for this purpose called profanity-check. Of course, before I did that, I looked in the Python Package Index (PyPI) for any existing libraries that could do this for me. The only half decent results for the search query “profanity” were: profanity (the ideal package name) better-profanity : “Inspired from package profanity of Ben
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