Analytics Vidhya
MARCH 25, 2020
Introduction “Efficiency is doing things right. Effectiveness is doing the right thing.” – Zig Zagler As data scientists, we are often taught to be. The post 10 Awesome Data Manipulation and Wrangling Hacks, Tips and Tricks appeared first on Analytics Vidhya.
KDnuggets
MARCH 23, 2020
We examine the growth of coronavirus daily cases in most affected countries, and show evidence that social distancing works in reducing the rate of spread. We also analyze KDnuggets Poll results - the scale of change to online and how Data Science work is likely to increase or drop in different regions. Stay Healthy and practice social distancing!
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Dataconomy
MARCH 23, 2020
In just one day, the HackCorona initiative gathered over 1700 people and 300 selected hackers came up with 23 digital solutions to help the world fight the COVID-19 outbreak during the 48-hour long virtual hackathon by Data Natives and Hacking Health. Here are the results. HackCorona was created on March 17th. The post HackCorona: 300 participants, 41 nationalities, 23 solutions to fight COVID-19 outbreak appeared first on Dataconomy.
Data Science 101
MARCH 23, 2020
Hilary Mason is the Founder of Fast Forward Labs. She has been involved in the data science space for over a decade. She is a real thought leader in the data space. This keynote was delivered at ODSC East 2020. The post Hilary Mason – The Future of AI and Machine Learning appeared first on Data Science 101.
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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have migrated their testing and production workloads to the cloud, yet development environments often remain tied to outdated local setups, limiting efficiency and growth.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.
Analytics Vidhya
MARCH 24, 2020
Overview Learn how to use graphs to identify social media influencers We will demonstrate several techniques to identify these social media influencers and lay. The post Using Graphs to Identify Social Media Influencers appeared first on Analytics Vidhya.
KDnuggets
MARCH 24, 2020
The deployment of large transformer-based models in dynamic commercial environments often yields poor results. This is because commercial environments are usually dynamic, and contain continuous domain shifts between inference and training data.
Data Science Current brings together the best content for data science professionals from the widest variety of thought leaders.
Eugene Yan
MARCH 27, 2020
Writing begins before actually writing; it's a cycle of reading -> note-taking -> writing.
Analytics Vidhya
MARCH 22, 2020
Google Colab – Now Build Large Deep Learning Models on your Machine! “Memory Error” – that all too familiar dreaded message in Jupyter notebooks. The post Free GPUs for Everyone! Get Started with Google Colab for Machine Learning and Deep Learning appeared first on Analytics Vidhya.
KDnuggets
MARCH 25, 2020
If your team has started using ?Ray? and you’re wondering what it is, this post is for you. If you’re wondering if Ray should be part of your technical strategy for Python-based applications, especially ML and AI, this post is for you.
Dataconomy
MARCH 24, 2020
Commercial and industrial applications of artificial intelligence and machine learning are unlocking economic opportunities, transforming the way we do business, and even helping to solve complex social and environmental problems. In fact, generative applications of this technology have become tools for environmental sustainability. With machine learning’s capability to analyze and.
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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?
Smart Data Collective
MARCH 24, 2020
Big data is changing the direction of our economy in unprecedented ways. Every business should look for ways to monetize big data and use it to optimize your business model. The number of companies using big data is growing at an accelerated rate. One poll found that 53% of businesses were using big data analytics in 2017. This figure has presumably risen in the years since.
Analytics Vidhya
MARCH 26, 2020
Unlocking a New World with the Support Vector Regression Algorithm Support Vector Machines (SVM) are popularly and widely used for classification problems in machine. The post Support Vector Regression Tutorial for Machine Learning appeared first on Analytics Vidhya.
KDnuggets
MARCH 23, 2020
TensorFlow Quantum allow data scientists to build machine learning models that work on quantum architectures.
DataRobot
MARCH 23, 2020
Data science teams are scrambling to update their models in the wake of extreme and unforeseen worldwide changes brought on by the global COVID-19 pandemic. In the face of these unprecedented events, one of the key concerns among many data scientists is that their current models could be generating inaccurate or misleading predictions. In the webinar, AI in Turbulent Times: Navigating Changing Conditions , we outlined the steps that data scientists can take to incorporate robustness into their m
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.
Smart Data Collective
MARCH 27, 2020
The auto insurance industry has always relied on data analysis to inform their policies and determine individual rates. With the technology available today, there’s even more data to draw from. The good news is that this new data can help lower your insurance rate. Here is the type of data insurance companies use to measure a client’s potential risk and determine rates.
Analytics Vidhya
MARCH 23, 2020
Introduction We are in the midst of a global crisis. The coronavirus, or COVID-19, has officially been declared a pandemic and it is wreaking. The post Coronavirus Analysis: Will Social Distancing Help Prevent the Spread? appeared first on Analytics Vidhya.
KDnuggets
MARCH 23, 2020
This is a short introduction to Made With ML, a useful resource for machine learning engineers looking to get ideas for projects to build, and for those looking to share innovative portfolio projects once built.
Data Science 101
MARCH 24, 2020
The world of data science is rapidly evolving. Here are a few data science papers I have found interesting. What’s Wrong with Computational Notebooks? Pain Points, Needs, and Design Opportunities This paper is a study done on the usage of notebooks for data science. It cover a bunch of the negative impacts of using notebooks for data science. Deployment, setup, collaboration, and reliablity are a few of the examples.
Speaker: Jay Allardyce, Deepak Vittal, and Terrence Sheflin
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.
Smart Data Collective
MARCH 23, 2020
Big data is driving a number of changes in our lives. Forbes recently wrote an article about the impact of big data on the food and hospitality industry. However, other sectors are changing as well. Big data phenomenon has revolutionized almost every aspect of an average citizen’s life. Information about our online activity has been accumulating for years, and now is actively used to know more about us.
Analytics Vidhya
MARCH 24, 2020
The Case for Building Trust in Machine Learning Models There are approximately 1.2 billion vehicles on the roads around the world. Here’s a bamboozling. The post 6 Python Libraries to Interpret Machine Learning Models and Build Trust appeared first on Analytics Vidhya.
KDnuggets
MARCH 25, 2020
This article aims to introduce one of the manifold learning techniques called Diffusion Map. This technique enables us to understand the underlying geometric structure of high dimensional data as well as to reduce the dimensions, if required, by neatly capturing the non-linear relationships between the original dimensions.
DataRobot Blog
MARCH 27, 2020
by Jen Underwood. NOTE: The following solution review is from a January 2020 project contract commitment. Both the vendor and I discussed the sensitive timing of publication. They decided not to cancel. Read More.
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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.
Smart Data Collective
MARCH 24, 2020
One of the most important elements in the evolution of the education system is the ability to make informed conclusions about the need to change approaches that are used and the actions that are taken. According to a 2015 whitepaper published in Science Direct , big data is one of the most disruptive technologies influencing the field of academia. The educational system continuously creates and accumulates a significant amount of data, and the question of the systematic work with these data by a
DataCentric podcast
MARCH 26, 2020
The Intelligent Edge, encompassing "devices that aren't in the datacenter", is growing at a nearly exponential rate. This challenges how traditional IT thinks about managing intelligent infrastructure, especially at the intersection of IT and OT, forcing everyone to think just a little bit differently -- all of this as nearly every company is forging their own paths.
KDnuggets
MARCH 24, 2020
Whether you are just learning Data Science, a current professional, or just interested, it's crucial to keep the mind stimulated and stay current. With conferences, schools, and travel largely canceled because of #coronavirus, these remote resources will help you stay engaged.
Explosion
MARCH 23, 2020
In this video, we’ll show you how you can use Prodigy to script fully custom annotation workflows in Python, how to plug in your own machine learning models and how to mix and match different interfaces for your specific use case.
Speaker: Nikhil Joshi, Founder & President of Snic Solutions
Is your manufacturing operation reaching its efficiency potential? A Manufacturing Execution System (MES) could be the game-changer, helping you reduce waste, cut costs, and lower your carbon footprint. Join Nikhil Joshi, Founder & President of Snic Solutions, in this value-packed webinar as he breaks down how MES can drive operational excellence and sustainability.
Smart Data Collective
MARCH 27, 2020
The supply chain is the source of every part of production. From raw materials to manufacturing to distribution, each step requires the most secure transition possible. Sometimes, though, the supply chain can come with various risks that affect these stages. Security issues arise from these vulnerabilities, and merchandise can be damaged or stolen, leading to more headaches and time-consuming procedures.
Data Science 101
MARCH 24, 2020
The world of data science is rapidly evolving. Here are a few data science papers I have found interesting. What’s Wrong with Computational Notebooks? Pain Points, Needs, and Design Opportunities This paper is a study done on the usage of notebooks for data science. It cover a bunch of the negative impacts of using notebooks for data science. Deployment, setup, collaboration, and reliablity are a few of the examples.
KDnuggets
MARCH 25, 2020
The best approach for AI production is similar to what venture capitalists (VC’s) do when they evaluate and invest in startups.
DataRobot
MARCH 25, 2020
Baseball very much remains America’s national pastime, but Major League Baseball (MLB) has faced its share of challenges recently. Even a franchise as universally successful and iconic as the Boston Red Sox -- four World Series championships since 2004 paired with massive popularity off the field -- is not immune to these challenges. To address some of these off-field obstacles, the Red Sox have turned to the same thing that helped them win those championships on the field: advanced analytics an
Speaker: Anindo Banerjea, CTO at Civio & Tony Karrer, CTO at Aggregage
When developing a Gen AI application, one of the most significant challenges is improving accuracy. This can be especially difficult when working with a large data corpus, and as the complexity of the task increases. The number of use cases/corner cases that the system is expected to handle essentially explodes. 💥 Anindo Banerjea is here to showcase his significant experience building AI/ML SaaS applications as he walks us through the current problems his company, Civio, is solving.
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