Sat.May 29, 2021 - Fri.Jun 04, 2021

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Develop your first Deep Learning Model in Python with Keras

Analytics Vidhya

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction An artificial Neural Network is a sub-field of Artificial Intelligence. The post Develop your first Deep Learning Model in Python with Keras appeared first on Analytics Vidhya.

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Towards Data Science - Author Spotlight with Eugene Yan

Eugene Yan

My favourite project, how I write weekly and how you can start, and content I would like to see more of.

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The Impact of Digital AI Advances on The New Workplace

Smart Data Collective

Artificial intelligence is the pillar of the new digital technology landscape. Since a growing number of companies are relying on digital technology for a variety of purposes, the impact this will have will be significant. There are a number of indicators that AI is going to be even more important in the near future. The role of the pandemic on the modern workplace cannot be overstated.

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Where chess pieces are most often captured

FlowingData

Reddit user desfirsit made heatmaps to show where on the chess board pieces are usually captured. The top two rows are for black pieces, and the bottom row is for white pieces. I’m no chess player, but this seems to look right? The frequency of captures appears to agree with movement patterns. Although I’m surprised that the queen, despite having the most freedom of movement, is often captured in the same place.

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Navigating the Future: Generative AI, Application Analytics, and Data

Generative AI is upending the way product developers & end-users alike are interacting with data. Despite the potential of AI, many are left with questions about the future of product development: How will AI impact my business and contribute to its success? What can product managers and developers expect in the future with the widespread adoption of AI?

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Will MLOps change the future of the healthcare system?

Analytics Vidhya

ArticleVideo Book This article was published as a part of the Data Science Blogathon Overview: From the advent of modern Science & Technology, Researchers are. The post Will MLOps change the future of the healthcare system? appeared first on Analytics Vidhya.

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Announcing Data Natives x VentureBeat – two AI powerhouse events in one

Dataconomy

You may already know about our Data Natives event. Last year, Europe’s biggest data science, AI, and machine learning conference brought over 5,000 attendees together to enjoy more than 150 speakers in 2020. And you may also know that VentureBeat is one of the world’s most famous tech publications. VentureBeat helps break the news.

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Colors of Bob Ross explored

FlowingData

Connor Rothschild charted all the colors Bob Ross used in The Joy of Painting : Most commonly, paintings have 12 colors. Of the 403 pieces in The Joy of Painting , 100 used 12 colors. The peak is concentrated around 12, meaning most of Ross’ paintings used somewhere in the range of 7-13 colors; very rarely did they venture outside of that range.

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A complete guide to doing Geospatial Analytics

Analytics Vidhya

ArticleVideo Book Introduction Today our phones resemble a genie’s lamp, a powerful wish-granting device at your fingertips! It can bring us anything and take. The post A complete guide to doing Geospatial Analytics appeared first on Analytics Vidhya.

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First Rule of Data Storytelling

The Data Administration Newsletter

Bedtime stories are as good as the problem they solve, every child will tell you that. Our children’s capacity to distinguish a good story from a bad one is not learned, but hardwired from birth. Storytellers and parents know this very well. It is just natural: humans have been telling stories for thousands of years, […].

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4 Great Programs Businesses Can Use to Get Accurate Data Results

Smart Data Collective

In 2016 experts projected that the “ big data ” industry would be worth somewhere around $30 billion by 2022. Based on last year’s data, that number has grown to $275 billion, and some experts expect it to be even higher after increases in computer usage and ecommerce due to the COVID pandemic forcing many companies to go remote and many consumers to do their shopping online, where data is collected for every purchase from pizza to a streaming movie.

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Get Better Network Graphs & Save Analysts Time

Many organizations today are unlocking the power of their data by using graph databases to feed downstream analytics, enahance visualizations, and more. Yet, when different graph nodes represent the same entity, graphs get messy. Watch this essential video with Senzing CEO Jeff Jonas on how adding entity resolution to a graph database condenses network graphs to improve analytics and save your analysts time.

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? Visualization Books for a Beginner – The Process 142

FlowingData

Welcome to issue #142 of The Process, the newsletter for FlowingData members about how the charts get made. I’m Nathan Yau, and this week I’m thinking about the books I’d recommend (and not recommend) to beginners who want to learn how to visualize data. Become a member for access to this — plus tutorials, courses, and guides.

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Integration of Python with Hadoop and Spark

Analytics Vidhya

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction Big data is the collection of data that is vast. The post Integration of Python with Hadoop and Spark appeared first on Analytics Vidhya.

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Ilan Gleiser: Predicting a World where Data and Technology Solve Economic Inequality

DataRobot

Will the future be a dystopia? A utopia? Or maybe a… protopia? . Those are among the fascinating topics I recently discussed with Ilan Gleiser. Gleiser is founder and CEO of Synarchy AI , where he works with businesses to help them benefit from machine learning and natural-language processing (NLP) to drive economic value, automate processes, and generate insights.

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Data Science Journey Walkthrough – From Beginner to Expert

Smart Data Collective

What is data science? Data science is analyzing and predicting data, It is an emerging field. Domain experts of all fields use it. Some of the applications of data science are driverless cars, gaming AI, movie recommendations, and shopping recommendations. Since the field covers such a vast array of services, data scientists can find a ton of great opportunities in their field.

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Understanding User Needs and Satisfying Them

Speaker: Scott Sehlhorst

We know we want to create products which our customers find to be valuable. Whether we label it as customer-centric or product-led depends on how long we've been doing product management. There are three challenges we face when doing this. The obvious challenge is figuring out what our users need; the non-obvious challenges are in creating a shared understanding of those needs and in sensing if what we're doing is meeting those needs.

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Writing about probability in a way that people will understand

FlowingData

We see probabilities mentioned in the news, in weather forecasts, during sporting events, political arguments, business reports, elections, medical advice, and scientific findings. But probability is a tricky concept that not all (most?) people understand. Grace Huckins for The Open Notebook outlines useful ways to communicate the numbers more clearly — to increase the chances readers do understand.

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How to Learn Mathematics For Machine Learning? What Concepts do You Need to Master in Data Science?

Analytics Vidhya

ArticleVideo Book This article was published as a part of the Data Science Blogathon Are you an aspiring data scientist who is fascinated by how. The post How to Learn Mathematics For Machine Learning? What Concepts do You Need to Master in Data Science? appeared first on Analytics Vidhya.

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Is Artificial Intelligence a Problem or an Opportunity?

The Data Administration Newsletter

Artificial Intelligence (AI) seems to have reached its peak, and yet it is still growing and reaching even the most remote parts of the world. There are countless benefits to this technology, including life-saving tools and systems that function with automated AI algorithms. However, some people are skeptical about the widespread and free use of […].

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Dear Laura: Should We Hire Full-Time Data Stewards?

Dataversity

Click to learn more about author Laura Madsen. Welcome to the Dear Laura blog series! As I’ve been working to challenge the status quo on Data Governance – I get a lot of questions about how it will “really” work. I’ll be sharing these questions and answers via this DATAVERSITY® series. Last year I wrote […]. The post Dear Laura: Should We Hire Full-Time Data Stewards?

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Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You Need to Know

Speaker: Timothy Chan, PhD., Head of Data Science

Are you ready to move beyond the basics and take a deep dive into the cutting-edge techniques that are reshaping the landscape of experimentation? 🌐 From Sequential Testing to Multi-Armed Bandits, Switchback Experiments to Stratified Sampling, Timothy Chan, Data Science Lead, is here to unravel the mysteries of these powerful methodologies that are revolutionizing how we approach testing.

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Machine Learning Transforms Life Insurance Beyond the Actuarial Process

Smart Data Collective

Many different industries are becoming more reliant on machine learning. The insurance industry is among those that has found new opportunities to take advantage of machine learning technology. Life insurance companies in particular are discovering the wondrous opportunities that AI provides, since this sector faces some unique challenges relative to other insurance offerings.

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Automated Machine Learning for Supervised Learning (Part 1)

Analytics Vidhya

ArticleVideo Book This article was published as a part of the Data Science Blogathon This. The post Automated Machine Learning for Supervised Learning (Part 1) appeared first on Analytics Vidhya.

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The Data-Centric Revolution: Fighting Class Proliferation

The Data Administration Newsletter

One of the ideas we promote is elegance in the core data model in a Data-Centric enterprise. This is harder than it sounds. Look at most application-centric data models: you would think they would be simpler than the enterprise model, after all, they are a small subset of it. Yet we often find individual application […].

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Considerations for Ensuring High Availability of Applications and Data

Dataversity

Click to learn more about author Dave Bermingham. When you think about how best to ensure the high availability (HA) of your applications and data, you need to think about more than just the speed with which you can failover to a standby system if your database suddenly fails. Yes, you should be prepared for full failover […]. The post Considerations for Ensuring High Availability of Applications and Data appeared first on DATAVERSITY.

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How Embedded Analytics Gets You to Market Faster with a SAAS Offering

Start-ups & SMBs launching products quickly must bundle dashboards, reports, & self-service analytics into apps. Customers expect rapid value from your product (time-to-value), data security, and access to advanced capabilities. Traditional Business Intelligence (BI) tools can provide valuable data analysis capabilities, but they have a barrier to entry that can stop small and midsize businesses from capitalizing on them.

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The Evolving Role of Analytics in Strategic Financial Management

Smart Data Collective

Analytics technology is becoming integral to the field of finance. The market for financial analytics services is projected to be worth over $11 billion within the next five years. Analytics is particularly important for developing strategic financial management policies. Strategic Financial Management or strategic finance is a process to help a company’s finances.

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4 Use Cases All Data Scientist Should Learn

Analytics Vidhya

ArticleVideo Book This article was published as a part of the Data Science Blogathon Illustrations of how to address traditional machine learning algorithm queries. Index. The post 4 Use Cases All Data Scientist Should Learn appeared first on Analytics Vidhya.

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Through the Looking Glass: Data Owners and Other Fallacies

The Data Administration Newsletter

I vividly remember reading this passage from Bob Seiner’s TDAN.com article “Things I Think I Think about Data Governance”, from August 1, 2015: If we were going to remove two words from the Data Governance vocabulary, I would choose the words “assign” and “owner. When someone is designated as the “owner” of data, that implies […].

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Is a Proactive Approach Best for Data Privacy and Cybersecurity?

Dataversity

Click to learn more about author Ashok Sharma. The dependence on the internet and the constant connection with cyberspace make personal data vulnerable to issues people and businesses are unaware of. Companies today are a storehouse for extensively valuable data – from employees’ data to the business’s financial data to corporate intelligence to customer information. […].

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Manufacturing Sustainability Surge: Your Guide to Data-Driven Energy Optimization & Decarbonization

Speaker: Kevin Kai Wong, President of Emergent Energy Solutions

In today's industrial landscape, the pursuit of sustainable energy optimization and decarbonization has become paramount. Manufacturing corporations across the U.S. are facing the urgent need to align with decarbonization goals while enhancing efficiency and productivity. Unfortunately, the lack of comprehensive energy data poses a significant challenge for manufacturing managers striving to meet their targets.

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When Big Data Meets Big Law – the Role of Data in Legal Services

Smart Data Collective

Many industries are starting to realize the true benefits they can get from analyzing and visualizing the many amounts of data is designed today. More and more conventional industries are starting to look into this direction: big data. One of these industries is the legal industry , with all legal companies and law firms included. There are some questions that legal advisors have: are there any real benefits of big data for law companies ?

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Emojize Your Data Science Projects

Analytics Vidhya

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction Our world is becoming more and more digital, especially after. The post Emojize Your Data Science Projects appeared first on Analytics Vidhya.

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Importance of Data Science in 2021

The Data Administration Newsletter

Data is critical for any business as it helps them make decisions based on trends, statistical numbers and facts. Due to this importance of data, data science as a multi-disciplinary field developed. It utilizes scientific approaches, frameworks, algorithms, and procedures to extract insight from a massive amount of data. These days, data science is the […].

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Not All Embedded Analytics and BI Solutions Are the Same

Dataversity

Click to learn more about author Daniel Jebaraj. Your enterprise software is outstanding in its functionality. You have a solid value proposition with your target market. To make your offering even more attractive, you’ve decided to embed analytics and business intelligence (ABI) into your product. So far, so good. But which embedded ABI solution will you select?

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From Developer Experience to Product Experience: How a Shared Focus Fuels Product Success

Speaker: Anne Steiner and David Laribee

As a concept, Developer Experience (DX) has gained significant attention in the tech industry. It emphasizes engineers’ efficiency and satisfaction during the product development process. As product managers, we need to understand how a good DX can contribute not only to the well-being of our development teams but also to the broader objectives of product success and customer satisfaction.