Sat.Oct 16, 2021 - Fri.Oct 22, 2021

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5 hot new IT jobs — and why they just might stick

DataKitchen

The post 5 hot new IT jobs — and why they just might stick first appeared on DataKitchen.

IT 356
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Diving Into the Future of Deep Learning: Exploring the Novel Challenges Title

Analytics Vidhya

This article was published as a part of the Data Science Blogathon Overview Though it is believed that tech enthusiasts are passing through the golden age of Artificial Intelligence, engineers and scientists still need to explore miles while progressing on their journey to Deep Learning projects. Either it is calibrating time-series models, processing Bayesian deep […].

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MLOps and DevOps: Why Data Makes It Different

O'Reilly on Data

Much has been written about struggles of deploying machine learning projects to production. As with many burgeoning fields and disciplines, we don’t yet have a shared canonical infrastructure stack or best practices for developing and deploying data-intensive applications. This is both frustrating for companies that would prefer making ML an ordinary, fuss-free value-generating function like software engineering, as well as exciting for vendors who see the opportunity to create buzz around a new

IT 352
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Use External Data Platform to Improve Analytics

David Menninger's Analyst Perspectives

Access to external data can provide a competitive advantage. Our research shows that more than three-quarters (77%) of participants consider external data to be an important part of their machine learning (ML) efforts. The most important external data source identified is social media, followed by demographic data from data brokers. Organizations also identified government data, market data, environmental data and location data as important external data sources.

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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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Tech workers warned they were going to quit. Now, the problem is spiralling out of control

DataKitchen

The post Tech workers warned they were going to quit. Now, the problem is spiralling out of control first appeared on DataKitchen.

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5 Features Of Snowflake That Data Engineers Must Know

Analytics Vidhya

This article was published as a part of the Data Science Blogathon Snowflake is a cloud data platform that comes with a lot of unique features when compared to traditional on-premise RDBMS systems. In this tutorial, you will see the top 5 features that developers should know before implementing a solution on the Snowflake data […]. The post 5 Features Of Snowflake That Data Engineers Must Know appeared first on Analytics Vidhya.

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Humans and AI: Bargaining Power

DataRobot

I have a confession to make—I’m a back-seat driver! When sitting in a taxi, I can’t help but grumble when the ride isn’t smooth, or the driver chooses the slowest lane of traffic. I have to fight the urge to take control. When it comes to shopping, I passively accept what is offered for sale. But my wife, who grew up in Asia where haggling is part of the culture, is different.

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Data Quality: Volume, interdependencies can create big problems

DataKitchen

The post Data Quality: Volume, interdependencies can create big problems first appeared on DataKitchen.

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Learn how to make your own Optical Illusion in Python

Analytics Vidhya

This article was published as a part of the Data Science Blogathon It was just past the midway mark of 2019 and the Internet casually decided to trick us as it normally does. An optical illusion went viral on Twitter which depicted a gray image that looked colored! Confused? Well, let’s dive deep in then! […]. The post Learn how to make your own Optical Illusion in Python appeared first on Analytics Vidhya.

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4 Reasons to Hire a Data Science Company

Smart Data Collective

1.145 trillion megabytes! Unbelievably, this is the amount of data that was created every day in 2021. That’s a lot of data and a lot of work for experts working in the field of data science services. Amidst growing competition, businesses are under increasing pressure to come up with unique and more cost-effective ways to manufacture and market their products.

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8 Steps to Transformation at Speed & Scale – Your Guide to Deploying StratOps

📌Is your Data & AI transformation struggling to really impact the business? Discover the game-changing StratOps approach that: Bridges the Gap : Connect your Data & AI strategy to your operating model, to ensure alignment at every level. Prioritizes Outcomes : Focuses on concrete business outcomes from day one, rather than capabilities in isolation.

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Introducing Self-Service, No-Code Airflow Authoring UI in Cloudera Data Engineering

Cloudera

Airflow has been adopted by many Cloudera Data Platform (CDP) customers in the public cloud as the next generation orchestration service to setup and operationalize complex data pipelines. Today, customers have deployed 100s of Airflow DAGs in production performing various data transformation and preparation tasks, with differing levels of complexity.

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Data Engineers are Burned Out and Calling for DataOps

DataKitchen

The post Data Engineers are Burned Out and Calling for DataOps first appeared on DataKitchen.

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An Easy introduction to Flask Framework for beginners

Analytics Vidhya

This article was published as a part of the Data Science Blogathon Overview What is a Framework FrontEnd vs BackEnd What is Flask Framework Installation of Flask Creating our first Flask app Routing Static Route vs Dynamic Route HTML Injections HTML Escaping Hypertext Transfer Protocol GET and POST Methods What is a Framework? The framework […].

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How Can Data-Centric UX Designers Make Better Games?

Smart Data Collective

Big data has touched almost every facet of our lives. It should be no surprise that the video gaming industry has been heavily influenced by developments in data technology. There are a number of potential opportunities to utilize big data in video games. One of the biggest benefits of integrating data analytics, AI and other technologies into video games is that it can help improve the user experience.

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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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How These Female Sales Leaders Are Blazing Their Own Trail: Meet Doreen, Natália, and Rachel

Dataiku

Ever wanted to know more about the people behind your favorite Everyday AI platform? You're in luck — every few weeks, meet some of the humans at Dataiku working to ensure customers and users find success as they systemize the use of data and AI in their organizations. This week, we spoke with three sales leaders: Doreen, RVP Inside Sales EMEA; Natália, RVP UK&I; and Rachel, VP Sales and General Manager Central Europe.

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Our 2021 Data Impact Awards Finalists

Cloudera

It’s that time of year again… Award season! We are thrilled to announce the finalists of the 2021 Data Impact Awards. This year’s entrants have excelled at demonstrating how innovative data solutions can help solve real-time challenges and positively impact people around the world. . The entries are some of the most remarkable we’ve seen, giving our judges the tough task of selecting an award worthy shortlist.

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10 Ideas that every Professional should avoid for Data Visualization

Analytics Vidhya

This article was published as a part of the Data Science Blogathon Image credits: Taras Bakusevych Data is the new oil we have heard it so many times. But can we visualize that data in a proper format? With the amount of data at our disposal today, the need to extract insights from it is […]. The post 10 Ideas that every Professional should avoid for Data Visualization appeared first on Analytics Vidhya.

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How AI and ML Can Transform Data Integration

Smart Data Collective

The data integration landscape is under a constant metamorphosis. In the current disruptive times, businesses depend heavily on information in real-time and data analysis techniques to make better business decisions, raising the bar for data integration. The upsurge of data (with the introduction of non-traditional data sources like streaming data, machine logs, etc.) along with traditional ones challenge old models of data integration.

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

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.

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Creating a Powerful Presentation: 3 Easy Changes to Revamp your PowerPoint

Depict Data Studio

Depict Data Studio full courses always end with a graduation ceremony where students share the progress they’ve made in the course. I’m always amazed by the transformations that take place and I can’t help but want to share their wonderful work! Today you’ll learn from Kelsey Watterson, an evaluator at the Centerstone Research Institute. Thanks for sharing Kelsey!

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What Is Mature MLOps? A Perspective

Dataiku

On a recent webinar with Jim Kobelius of TDWI (that you can watch below), we talked about mature MLOps. You can watch our presentations, but I thought it would be helpful to summarize some of the concepts based on over ten years working with machine learning and, over the last three and a half years, specifically focusing on MLOps.

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Introduction to Matplotlib using Python for Beginners

Analytics Vidhya

This article was published as a part of the Data Science Blogathon Introduction to Matplotlib If you are interested in data analytics or data visualization you are at the right place to get started. So let’s start with the simple introduction about, Data visualization which is the process of translating the numbers, text, or large data […].

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4 Certificates Data Security Enthusiasts Should Consider

Smart Data Collective

Data security has become a greater concern than ever in recent years. There were only 662 data breaches in 2010. That number rose to over 1,000 by last year. The rising number of data breaches has created a strong demand for data security professionals. The unfortunate truth is that we need more big data professionals than ever. The shortage of data-savvy security experts is actually holding the United States and other countries back.

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Improving the Accuracy of Generative AI Systems: A Structured Approach

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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PODCAST: AI for Digital Enterprise – Part 1- A Practitioner’s View on AI-Led Transformation in Manufacturing

bridgei2i

A Practitioner’s View on AI-Led Transformation in Manufacturing. Aditya Karnani, Lead, Factory Performance & Reliability, Colgate Palmolive | Ronobijay Bhaumik, Director, Digital Consulting, Intelligent Operations, BRIDGEi2i. Subscribe Now. Highlights. In this podcast, the guest Adita Karnani shares some thought-provoking insights on AI-led automation in manufacturing plants and how digitalization coupled with the pandemic has led to innovations and processes within many industrial plants. [

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Joining Datasets With Imprecise Data: The Benefits of Fuzzy Join Using a Fuzzy Matching Algorithm

Dataiku

Imagine that you’re just about to buy a new shirt at your local big box retailer. “Do you have an account with us?” asks the cashier. You think you may have signed up before, but can’t really remember.

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An End-to-End Introduction to Generative Adversarial Networks(GANs)

Analytics Vidhya

This article was published as a part of the Data Science Blogathon There are many ways a machine can be taught to generate an output on unseen data. The technological advancement in different sectors has left everyone shocked. we are now at a point where deep learning and neural networks are so powerful that can […]. The post An End-to-End Introduction to Generative Adversarial Networks(GANs) appeared first on Analytics Vidhya.

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5 Proven Tips To Use Analytics to Improve Your Website in 2021

Smart Data Collective

Analytics technology has become more important than ever in shaping the future of business. Countless businesses are looking for new ways to apply analytics technology to improve every aspect of their business model. One of the most important applications of analytics is with website management and development. You can use analytics to optimize your website to become more aesthetically pleasing to viewers.

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What Is Entity Resolution? How It Works & Why It Matters

Entity Resolution Sometimes referred to as data matching or fuzzy matching, entity resolution, is critical for data quality, analytics, graph visualization and AI. Learn what entity resolution is, why it matters, how it works and its benefits. Advanced entity resolution using AI is crucial because it efficiently and easily solves many of today’s data quality and analytics problems.

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Five Ways AI Can Help States Solve Their Hardest Problems (Part 2): Mitigate Risk and Fraud

DataRobot

In part one of our “Five Ways AI Can Help States Solve Their Hardest Problems” blog series, we reviewed the ramifications of crisis response management—or lack thereof—and how AI can help. As part of the COVID-19 crisis response, the federal government has provided aid to states and localities by designating federal recovery funds. Consequently, the influx of recovery funds is now resulting in increased fraud, waste, and abuse across government—including social services—preventing dollars from g

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Why AI Is Essential to the New Energy Model

Dataiku

Between energy diversity, climate challenges, and growth in electricity consumption, energy producers and suppliers must constantly optimize their processes and anticipate demand in order to adjust their offers, a strategy based on massive data collection and the deployment of AI solutions. Today it is impossible to master the complexity of the energy ecosystem without using data science.

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Forest Fire prediction using Machine Learning

Analytics Vidhya

This article was published as a part of the Data Science Blogathon What does this article entail? Forest, bush, or vegetarian fire, can be described as any uncontrolled and non-prescribed combustion or burning of plants in a natural setting such as a forest, grassland, etc. In this article we are not determining if a forest […]. The post Forest Fire prediction using Machine Learning appeared first on Analytics Vidhya.

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What is Yield Farming in Crypto and How Does Data Analytics Help?

Smart Data Collective

Data analytics has become a major gamechanger for the cryptocurrency industry. Traders and miners have discovered a number of advantages of using big data and AI tools to improve their profitability. One of the newest applications of data analytics in cryptocurrency mining is with yield farming. Many crypto enthusiasts have found that it can help them lift their ROI considerably and address many of the problems that they face.

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Data Modeling for Direct Mail: Boosting Multi-Channel Reach and Response

Speaker: Jesse Simms, VP at Giant Partners

This new, thought-provoking webinar will explore how even incremental efforts and investments in your data can have a tremendous impact on your direct mail and multi-channel marketing campaign results! Industry expert Jesse Simms, VP at Giant Partners, will share real-life case studies and best practices from client direct mail and digital campaigns where data modeling strategies pinpointed audience members, increasing their propensity to respond – and buy.