Sat.Sep 14, 2019 - Fri.Sep 20, 2019

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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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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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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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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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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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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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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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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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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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9 Powerful Tips and Tricks for Working with Image Data using skimage in Python

Analytics Vidhya

Overview New to working with image data? The skimage module in Python is an ideal starting point Learn 8 simple yet powerful tricks for. The post 9 Powerful Tips and Tricks for Working with Image Data using skimage in Python appeared first on Analytics Vidhya.

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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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Apache Airflow®: The Ultimate Guide to 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!

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How Up-And-Coming Music Companies Use Big Data For Optimal Results

Smart Data Collective

Big data has brought major changes to countless industries. Healthcare, finance, criminal justice, and manufacturing have all been touched by advances in big data. However, big data is also transforming other industries. The music industry is relying more on big data than ever. Darren Heitner wrote a great article on Inc. About the way that big data is revolutionizing the industry.

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My journey path from a Software Engineer to BI Specialist to a Data Scientist

KDnuggets

The career path of the Data Scientist remains a hot target for many with its continuing high demand. Becoming one requires developing a broad set of skills including statistics, programming, and even business acumen. Learn more about one person's experience making this journey, and discover the many resources available to help you find your way into a world of data science.

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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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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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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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AI Paves The Road For Incredible Changes In The Gaming Industry

Smart Data Collective

I recently read a great post from The Verge on the impact of AI on the video gaming industry. Author Nick Statt made a great point about the evolution of AI in the industry. Pratt pointed out that AI has been a factor in the video game industry since the very beginning. Some of the AI tools that we see today resemble those in the 1980 game Rogue. Of course, AI has improved dramatically over the last 40 years.

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How Bad is Multicollinearity?

KDnuggets

For some people anything below 60% is acceptable and for certain others, even a correlation of 30% to 40% is considered too high because it one variable may just end up exaggerating the performance of the model or completely messing up parameter estimates.

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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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DataRobot Announces Series E Funding Round

DataRobot

Today, we announced that we have raised $206M in Series E financing. This new capital will significantly accelerate our ability to execute on our vision of helping all organizations become AI-driven. I want to briefly summarize why we raised this additional capital and how we plan to execute on this vision.

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15 Modern Use Cases for Enterprise Business Intelligence

Large enterprises face unique challenges in optimizing their Business Intelligence (BI) output due to the sheer scale and complexity of their operations. Unlike smaller organizations, where basic BI features and simple dashboards might suffice, enterprises must manage vast amounts of data from diverse sources. What are the top modern BI use cases for enterprise businesses to help you get a leg up on the competition?

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5 Benefits Of Machine Learning In Enterprise Electrical Systems

Smart Data Collective

Machine learning is creating pivotal change in the energy industry. Towards Data Science wrote about the changes that machine learning is bringing to this field. They pointed out that Bill Gates wrote a letter in 2017 to graduate students across the country, which stated that machine learning is going to be the biggest disruptor in this industry. You need to consider the benefits of using an electrical system that relies on machine learning technology.

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A Gentle Introduction to PyTorch 1.2

KDnuggets

This comprehensive tutorial aims to introduce the fundamentals of PyTorch building blocks for training neural networks.

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5 Beginner Friendly Steps to Learn Machine Learning and Data Science with Python

KDnuggets

“I want to learn machine learning and artificial intelligence, where do I start?” Here.

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The Hidden Risk of AI and Big Data

KDnuggets

With recent advances in AI being enabled through access to so much “Big Data” and cheap computing power, there is incredible momentum in the field. Can big data really deliver on all this hype, and what can go wrong?

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Marketing Operations in 2025: A New Framework for Success

Speaker: Mike Rizzo, Founder & CEO, MarketingOps.com and Darrell Alfonso, Director of Marketing Strategy and Operations, Indeed.com

Though rarely in the spotlight, marketing operations are the backbone of the efficiency, scalability, and alignment that define top-performing marketing teams. In this exclusive webinar led by industry visionaries Mike Rizzo and Darrell Alfonso, we’re giving marketing operations the recognition they deserve! We will dive into the 7 P Model —a powerful framework designed to assess and optimize your marketing operations function.

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The 5 Sampling Algorithms every Data Scientist need to know

KDnuggets

Algorithms are at the core of data science and sampling is a critical technical that can make or break a project. Learn more about the most common sampling techniques used, so you can select the best approach while working with your data.

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5 Alternative Data Science Tools

KDnuggets

What other creative tools for data science beyond Python and R can you use to make an impression? It's not about the tool -- it's about its impact.

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Automate Hyperparameter Tuning for Your Models

KDnuggets

When we create our machine learning models, a common task that falls on us is how to tune them. So that brings us to the quintessential question: Can we automate this process?

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What is Machine Behavior?

KDnuggets

The new emerging field that wants to study AI agents the way social scientists study humans.

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Prepare Now: 2025s Must-Know Trends For Product And Data Leaders

Speaker: Jay Allardyce, Deepak Vittal, Terrence Sheflin, and Mahyar Ghasemali

As we look ahead to 2025, business intelligence and data analytics are set to play pivotal roles in shaping success. Organizations are already starting to face a host of transformative trends as the year comes to a close, including the integration of AI in data analytics, an increased emphasis on real-time data insights, and the growing importance of user experience in BI solutions.

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Cartoon: Unsupervised Machine Learning?

KDnuggets

New KDnuggets Cartoon looks at one of the hottest directions in Machine Learning and asks can Machine Learning be too unsupervised?

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Top KDnuggets tweets, Sep 11-17: Python Libraries for Interpretable Machine Learning

KDnuggets

Also: Cartoon: Unsupervised #MachineLearning?; Cartoon: Unsupervised Machine Learning ? How to Become More Marketable as a Data Scientist; Ensemble Methods for Machine Learning: AdaBoost.

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Scikit-Learn & More for Synthetic Dataset Generation for Machine Learning

KDnuggets

While mature algorithms and extensive open-source libraries are widely available for machine learning practitioners, sufficient data to apply these techniques remains a core challenge. Discover how to leverage scikit-learn and other tools to generate synthetic data appropriate for optimizing and fine-tuning your models.

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5 Step Guide to Scalable Deep Learning Pipelines with d6tflow

KDnuggets

How to turn a typical pytorch script into a scalable d6tflow DAG for faster research & development.

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The Cloud Development Environment Adoption Report

Cloud Development Environments (CDEs) are changing how software teams work by moving development to the cloud. Our Cloud Development Environment Adoption Report gathers insights from 223 developers and business leaders, uncovering key trends in CDE adoption. With 66% of large organizations already using CDEs, these platforms are quickly becoming essential to modern development practices.