September, 2019

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Know Your Data: Part 1

KDnuggets

This article will introduce the different type of data sets, data object and attributes.

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4 Unique Methods to Optimize your Python Code for Data Science

Analytics Vidhya

Overview Writing optimized Python code is a crucial piece in your data science skillset Here are four methods to optimize your Python code (with. The post 4 Unique Methods to Optimize your Python Code for Data Science appeared first on Analytics Vidhya.

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Lessons from the Basketball Court for Data Management

Dataconomy

A data management plan in a company is not something that can be implemented in isolation by one department or a team in your organisation, it is rather a collective effort – similar to how different players perform in a basketball court. From the smallest schoolyard to the biggest pro. The post Lessons from the Basketball Court for Data Management appeared first on Dataconomy.

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The Role of Big Data In The Maintenance Industry

Smart Data Collective

As industry buzzwords, “Big Data” is one of those phrases that has become seemingly ubiquitous. Everyone wants to be using big data to better their operation. The maintenance department is no exception to this trend. Accordingly, maintenance teams are beginning to embrace the use of big data and analytics to improve performance. In emphasizing the use of “big data”, maintenance can establish predictive maintenance programs, which reduce downtime and save on maintenance costs.

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What’s New in Apache Airflow® 3.0—And How Will It Reshape Your Data Workflows?

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.

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Coursera Course for AWS Machine Learning

Data Science 101

Amazon and Coursera have teamed up to create Getting Started with AWS Machine Learning. Topics covered are: Machine Learning. Computer Vision. NLP. Amazon Sagemaker. Happy Learning!

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OMSCS CS6750 (Human Computer Interaction) Review and Tips

Eugene Yan

OMSCS CS6750 (Human Computer Interaction) - You are not your user! Or how to build great products.

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More Trending

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A Data Scientist’s Guide to 8 Types of Sampling Techniques

Analytics Vidhya

Overview Sampling is a popular statistical concept – learn how it works in this article We will also talk about eight different types of. The post A Data Scientist’s Guide to 8 Types of Sampling Techniques appeared first on Analytics Vidhya.

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Everything you want to know about GDPR’s Right to be Forgotten in Blockchain

Dataconomy

What is the big problem with the right to be forgotten (right to erasure, Article 17) under the GDPR? As Blockchain generally is immutable, and the GDPR requires personal data to be deleted – many people therefore conclude that it is impossible to store any kind of personal data on. The post Everything you want to know about GDPR’s Right to be Forgotten in Blockchain appeared first on Dataconomy.

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Big Data Paves The Road For A New Generation Of Investing Apps

Smart Data Collective

Big data is changing the financial industry in a truly astounding way. Countless financial professionals are looking towards machine learning and other new tools to improve the quality of the services that they offer to their customers. K. Hussain of Atos Spain published a white paper on the growing relevance of big data in the finance and insurance verticals.

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Open Source Data Science Projects 2019

Data Science 101

A number of new impactful open source projects have been released lately. Open Source Data Science Projects. Pythia – from Facebook for deep learning with vision and language, “such as answering questions related to visual data and automatically generating image captions “ InterpretML – from Microsoft, ” package for training interpretable models and explaining blackbox systems “ ML framework for Julia – from Alan Turing Institute, MLJ is a machine learni

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Agent Tooling: Connecting AI to Your Tools, Systems & Data

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.

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Introducing DataRobot AI Catalog

DataRobot

Data is the fuel that drives high-scale innovation with AI. Enterprises that put a strategy in place encouraging a culture of collaboration and sharing of their data assets will benefit the most. These organizations will see exponential gains in productivity with AI. Their employees will work together on projects, sharing their ideas, things they create, and their domain expertise.

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5 Famous Deep Learning Courses/Schools of 2019

KDnuggets

Deep Learning is/has become the hottest skill in Data Science at the moment. There is a plethora of articles, courses, technologies, influencers and resources that we can leverage to gain the Deep Learning skills.

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A Beginner-Friendly Guide to PyTorch and How it Works from Scratch

Analytics Vidhya

Overview What is PyTorch? How can you get started with it from scratch? We’ll cover all of that in this article PyTorch is one. The post A Beginner-Friendly Guide to PyTorch and How it Works from Scratch appeared first on Analytics Vidhya.

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The Rise Of “Menstrual Surveillance” and the Fight for Data Privacy in Women’s Health

Dataconomy

Before you start using the next amazing new femtech innovation, you may want to weigh the benefits against your right to privacy. You might want to think twice before accepting that sweet employer incentive for participating in health monitoring. Yes. Corporate wellness monitoring programs offer benefits, but they also have. The post The Rise Of “Menstrual Surveillance” and the Fight for Data Privacy in Women’s Health appeared first on Dataconomy.

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How to Modernize Manufacturing Without Losing Control

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

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How Big Data Is Transforming Social Media Marketing

Smart Data Collective

Big Data is among one of the most impressive tech advancements that have hit the marketing world in recent memory. While it has been tossed around as a buzzword in certain circles, Big Data is so much more than just a phrase. For a definition , Oracle recommends Gartner’s 2001 description of Big Data, which describes it as data containing a greater variety, getting to the source in increasing volume and at ever-higher velocity.

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5 great Data Strategy Resources

Data Science 101

I am putting together some of my own resources on Data Strategy. Here are a few of the top resources I found helpful so far. What is a Data Strategy? – various definitions of a data strategy The 5 essential Components of a Data Strategy – a detailed whitepaper(PDF) from SAS How to Create a Successful Data Strategy – a detailed report from MIT How Do You Develop a Data Strategy (including 6 steps) – by Bernard Marr, He has created more data strategies than anyone, so his a

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Announcing DataRobot MLOps

DataRobot

The truth is that the work of data scientists cannot generate value if the models never make it to production. For data scientists writing custom models in languages like Python and R, the number of challenges for getting models into production can be overwhelming. Issues range from how to deploy model code on production systems, how to monitor performance, and how to deploy updates to models over time.

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Which Data Science Skills are core and which are hot/emerging ones?

KDnuggets

We identify two main groups of Data Science skills: A: 13 core, stable skills that most respondents have and B: a group of hot, emerging skills that most do not have (yet) but want to add. See our detailed analysis.

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Automation, Evolved: Your New Playbook for Smarter Knowledge Work

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.

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Everything you Should Know about p-value from Scratch for Data Science

Analytics Vidhya

Overview What is p-value? Where is it used in data science? And how can we calculate it? We answer all these questions and more. The post Everything you Should Know about p-value from Scratch for Data Science appeared first on Analytics Vidhya.

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Three Trends in E-commerce Payments to be Concerned About

Dataconomy

With ecommerce sales skyrocketing, the options for online transactions are manifold. But what are the problems that come with these many choices to pay? Find out. Global e-commerce sales hit $29 trillion in 2017 according to data released by the United Nations Conference on Trade and Development (UNCTAD) early this. The post Three Trends in E-commerce Payments to be Concerned About appeared first on Dataconomy.

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Machine Learning Is The Latest Stage Of Text To Speech Technology

Smart Data Collective

Machine learning has played a very important role in the development of technology that has a large impact on our everyday lives. However, machine learning is also influencing the direction of technology that is not as commonplace. Text to speech technology is a prime example. Text to speech technology predates machine learning by over a century. However, machine learning has made the technology more reliable than ever.

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Nuts About Data Book Review

Data Science 101

Just released this week, Nuts about Data , is a fun introductory book about the data science process. Meor Amer tells a witty story about squirrels, mining for nuts, teamwork, and survival. It brings together the entire data science lifecycle from asking questions to final storytelling. It is a quick read and really fun. I highly recommend it and hope you enjoy it.

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The 2nd Generation of Innovation Management: A Survival Guide

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?

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DataRobot Automated Feature Engineering

DataRobot

In release 5.2 , DataRobot brings the next-generation of automated feature engineering capabilities to its flagship Automated Machine Learning and Automated Time Series products.

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BERT, RoBERTa, DistilBERT, XLNet: Which one to use?

KDnuggets

Lately, varying improvements over BERT have been shown — and here I will contrast the main similarities and differences so you can choose which one to use in your research or application.

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Here are 7 Data Science Projects on GitHub to Showcase your Machine Learning Skills!

Analytics Vidhya

Overview Working on Data Science projects is a great way to stand out from the competition Check out these 7 data science projects on. The post Here are 7 Data Science Projects on GitHub to Showcase your Machine Learning Skills! appeared first on Analytics Vidhya.

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A Simple and Transparent Machine Learning Approach Proves to Conquer the German Market

Dataconomy

Vice-President of XING’s Data Science team, Dr. Sébastien Foucaud, believes the time of blackbox AI is behind us. The market leader in the DACH region has a vision for its Machine Learning: it should be explainable to the boss, as well as to users. Focussing on German-speaking countries since 2012, The post A Simple and Transparent Machine Learning Approach Proves to Conquer the German Market appeared first on Dataconomy.

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Optimizing The Modern Developer Experience with Coder

Many software teams have migrated their testing and production workloads to the cloud, yet development environments often remain tied to outdated local setups, limiting efficiency and growth. This is where Coder comes in. In our 101 Coder webinar, you’ll explore how cloud-based development environments can unlock new levels of productivity. Discover how to transition from local setups to a secure, cloud-powered ecosystem with ease.

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The Role of Big Data In The Promotion of eLearning Courses

Smart Data Collective

We have talked extensively about the role of big data in marketing in previous articles. However, most of our articles relate to the use of big data with traditional marketing channels, including older digital marketing outlets. There are a number of new channels that use big data as well. Push notifications are among them. Hacker Moon wrote an article on the role of big data with push notifications.

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Git Aliases I Use (Because I'm Lazy)

Victor Zhou

I finally started using Git more heavily a few years ago when I first began building some of my bigger side projects. Now, it’s true that typing git status and git push is pretty easy, but if you’ve got some Git experience you know some commands can get rather long. The one that always got me was: $ git commit --amend --no-edit This amends your staged changes into your most recent commit without changing its commit message (so Git won’t open a text editor!).

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Lights, Cameras, Data: Predicting Winners for the 2019 Primetime Emmy Awards

DataRobot

This blog is meant to be a fun and unique take on predicting Outstanding Drama and Comedy Series for the 2019 Primetime Emmy Awards.

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Explore the world of Bioinformatics with Machine Learning

KDnuggets

The article contains a brief introduction of Bioinformatics and how a machine learning classification algorithm can be used to classify the type of cancer in each patient by their gene expressions.

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Apache Airflow® Best Practices: DAG Writing

Speaker: Tamara Fingerlin, Developer Advocate

In this new webinar, Tamara Fingerlin, Developer Advocate, will walk you through many Airflow best practices and advanced features that can help you make your pipelines more manageable, adaptive, and robust. She'll focus on how to write best-in-class Airflow DAGs using the latest Airflow features like dynamic task mapping and data-driven scheduling!