Data Science Tech Brief By HackerNoon

Data Science Tech Brief By HackerNoon

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Data Science Tech Brief By HackerNoon episodes

  • Special Database 18: What Is It and How Does It Work?

    This story was originally published on HackerNoon at: https://hackernoon.com/special-database-18-what-is-it-and-how-does-it-work.


    This dataset contains black-and-white mugshot photographs of 1,573 people. The 3,248 undated photos appear to be many decades old...
    Check more stories related to data-science at: https://hackernoon.com/c/data-science.
    You can also check exclusive content about #data, #special-database-18, #public-data, #nist, #photo-database, #the-markup, #mugshots, #public-records-database, and more.


    This story was written by: @TheMarkup. Learn more about this writer by checking @TheMarkup's about page,
    and for more stories, please visit hackernoon.com.


    This dataset contains black-and-white mugshot photographs of 1,573 people. The 3,248 undated photos appear to be many decades old and to come from a variety of locations. The photos feature front and profile views of people and are accompanied by a metadata file containing the subject’s gender and age at the time of the photo.

    13 min
  • Spotify Wrapped Hack: Create Your Own Stats Before the Official Release

    This story was originally published on HackerNoon at: https://hackernoon.com/spotify-wrapped-hack-create-your-own-stats-before-the-official-release.


    Use your streaming history to generate your own Spotify streaming stats like most listened-to songs, artists, and albums.
    Check more stories related to data-science at: https://hackernoon.com/c/data-science.
    You can also check exclusive content about #python-programming, #spotify-stats, #jupyter-notebook, #data-analysis, #spotify-wrapped-hack, #spotify-data-trick, #make-your-own-spotify-wrapped, #hackernoon-top-story, #hackernoon-es, #hackernoon-hi, #hackernoon-zh, #hackernoon-fr, #hackernoon-bn, #hackernoon-ru, #hackernoon-vi, #hackernoon-pt, #hackernoon-ja, #hackernoon-de, #hackernoon-ko, #hackernoon-tr, and more.


    This story was written by: @lukaskrimphove. Learn more about this writer by checking @lukaskrimphove's about page,
    and for more stories, please visit hackernoon.com.


    This is a way to get a sneak peek at your Spotify statistics before the official release of Spotify Wrapped. Learn how to use your streaming history to uncover the songs, artists, and albums you have listened to the most.

    4 min
  • Data Representation Techniques for Efficient Query Performance

    This story was originally published on HackerNoon at: https://hackernoon.com/data-representation-techniques-for-efficient-query-performance.


    Discover how to boost Apache Spark's query efficiency using data sketches for fast counts and intersections in large datasets. Essential for data pros!
    Check more stories related to data-science at: https://hackernoon.com/c/data-science.
    You can also check exclusive content about #big-data, #data-engineering, #apache-spark, #query-performance, #big-data-analytics, #data-representation, #data-structures-and-algorithms, #data-representation-techniques, and more.


    This story was written by: @vpenikal. Learn more about this writer by checking @vpenikal's about page,
    and for more stories, please visit hackernoon.com.


    Apache Spark is renowned for its ability to handle large-scale data processing. The key to unlocking its full potential lies in understanding and leveraging effective data representation strategies. We will explore the role of data sketches, a powerful technique that offers a revolutionary approach to streamlining counts, intersections, and union computations.

    8 min
  • 13 Best Datasets for Power BI Practice

    This story was originally published on HackerNoon at: https://hackernoon.com/13-best-datasets-for-power-bi-practice.


    In 2022, Gartner named Microsoft Power BI the Business Intelligence and Analytics Platforms leader. These are the 13 Best Datasets for Power BI Practice.
    Check more stories related to data-science at: https://hackernoon.com/c/data-science.
    You can also check exclusive content about #datasets, #power-bi, #data-science, #big-data, #data-analysis, #data-visualization, #dataset, #machine-learning, and more.


    This story was written by: @datasets. Learn more about this writer by checking @datasets's about page,
    and for more stories, please visit hackernoon.com.


    In 2022, Gartner named Microsoft Power BI the Business Intelligence and Analytics Platforms leader. With the aid of business intelligence tools, unstructured data can go through extraction, cleaning, and analysis processes to create insights that help organizations make data-driven decisions. In this article, we look at the 13 Best Datasets for Power BI Practice.

    18 min
  • Navigating Big Data's Potential and Privacy in Modern Medicine

    This story was originally published on HackerNoon at: https://hackernoon.com/navigating-big-datas-potential-and-privacy-in-modern-medicine.


    How can we harness big data to advance healthcare while protecting sensitive patient information? This article explores and answers that question.
    Check more stories related to data-science at: https://hackernoon.com/c/data-science.
    You can also check exclusive content about #big-data, #data-security, #digital-health, #healthtech, #patientprivacy, #datadrivenhealth, #personalizedmedicine, #medical-data-warehouse, and more.


    This story was written by: @viktoriaerokhina. Learn more about this writer by checking @viktoriaerokhina's about page,
    and for more stories, please visit hackernoon.com.


    The healthcare industry is experiencing rapid change thanks to the rise of big data. Big data refers to the massive amounts of information generated from electronic health records, wearable devices, genetic testing, social media, and more.
    This data has tremendous potential to improve diagnosis, enable predictive analytics, allow for personalized medicine, and further medical research. However, along with these benefits come significant risks, especially regarding patient privacy and data security.

    14 min
  • My Notes on MAE vs MSE Error Metrics 🚀

    This story was originally published on HackerNoon at: https://hackernoon.com/my-notes-on-mae-vs-mse-error-metrics.


    We will focus on MSE and MAE metrics, which are frequently used model evaluation metrics in regression models.
    Check more stories related to data-science at: https://hackernoon.com/c/data-science.
    You can also check exclusive content about #data-science, #metrics, #linear-regression, #error-metrics, #machine-learning, #regularization, #normal-distribution, #residuals, #hackernoon-es, and more.


    This story was written by: @sengul. Learn more about this writer by checking @sengul's about page,
    and for more stories, please visit hackernoon.com.


    We will focus on MSE and MAE metrics, which are frequently used model evaluation metrics in regression models. MAE is the average distance between the real data and the predicted data, but fails to punish large errors in prediction. MSE measures the average squared difference between the estimated values and the actual value. L1 and L2 Regularization is a technique used to reduce the complexity of the model. It does this by penalizing the loss function by regularizing the function of the function.

    11 min
  • Assessing Your Organization's Customer Data Maturity

    This story was originally published on HackerNoon at: https://hackernoon.com/assessing-your-organizations-customer-data-maturity.


    Investing in customer data is a top priority for marketing leaders.
    Check more stories related to data-science at: https://hackernoon.com/c/data-science.
    You can also check exclusive content about #customer-data, #customer-data-management, #customer-data-maturity, #database, #data-analysis, #data-visualization, #data-protection, #good-company, #hackernoon-es, and more.


    This story was written by: @mparticle. Learn more about this writer by checking @mparticle's about page,
    and for more stories, please visit hackernoon.com.


    Marketing departments are still trying to make sense of customer data they’re collecting, reduce manual work required to support customer data processes, and figure out how to use customer data to increase customer value. The Gartner CMO Council report surveyed 300 marketing leaders across industries and geographies and found that 80% of leaders said data, analytics and insights are “very important to winning and retaining customers,” nearly two-thirds were only moderately confident (or worse) in their data systems. To prevent your customer data set from becoming a data swamp, lay a solid, scalable customer data infrastructure at the heart of your martech stack.

    15 min
  • From Hadoop to Cloud: Why and How to Decouple Storage and Compute in Big Data Platforms

    This story was originally published on HackerNoon at: https://hackernoon.com/from-hadoop-to-cloud-why-and-how-to-decouple-storage-and-compute-in-big-data-platforms.


    This article reviews the Hadoop architecture, discusses the importance and feasibility of storage-compute decoupling, and explores available market solutions.
    Check more stories related to data-science at: https://hackernoon.com/c/data-science.
    You can also check exclusive content about #data, #open-source, #big-data, #distributed-systems, #distributed-file-systems, #object-storage, #cloud-native, #software-architecture, and more.


    This story was written by: @suave. Learn more about this writer by checking @suave's about page,
    and for more stories, please visit hackernoon.com.


    Initially, Hadoop integrated storage and compute, but the emergence of cloud computing led to a separation of these components. Object storage emerged as an alternative to HDFS but had limitations. To complement these limitations, JuiceFS, an open source distributed file system, offers cost-effective solutions for data-intensive scenarios like computation, analysis, and training. The decision to adopt storage-compute separation depends on factors like scalability, performance, cost, and compatibility.

    21 min
  • Embracing the Shift: Future of Work in the Era of Automation

    This story was originally published on HackerNoon at: https://hackernoon.com/embracing-the-shift-future-of-work-in-the-era-of-automation.


    Embracing the changing face of work: understanding automation's influence and equipping yourself with skills for the future.
    Check more stories related to data-science at: https://hackernoon.com/c/data-science.
    You can also check exclusive content about #data-analysis, #automation, #software-development, #ai, #future-of-work, #artificial-intelligence, #work, #machine-learning, and more.


    This story was written by: @vikrantbhalodia. Learn more about this writer by checking @vikrantbhalodia's about page,
    and for more stories, please visit hackernoon.com.


    The landscape of work is rapidly shifting due to automation across the industries. While certain jobs will be rendered obsolete by automation, employment prospects, such as custom software development, will emerge. The key for professionals lies in the adaptability and the development of skills that are highly sought after in the emerging future.

    4 min
  • Is Data Licensing the Key to the Privacy-Personalization Paradox?

    This story was originally published on HackerNoon at: https://hackernoon.com/is-data-licensing-the-key-to-the-privacy-personalization-paradox.


    Consumers want both privacy and personalization. Is it possible? Of course. As data becomes an asset for consumers, data licenses may bring both worlds together
    Check more stories related to data-science at: https://hackernoon.com/c/data-science.
    You can also check exclusive content about #data, #personalization, #privacy, #data-privacy, #customer-loyalty, #digital-asset, #data-science, #user-data-privacy, and more.


    This story was written by: @shanefaria. Learn more about this writer by checking @shanefaria's about page,
    and for more stories, please visit hackernoon.com.


    Consumers want personalization AND they want privacy. But they're still willing to share data for personalized experiences, perks, deals, and benefits. As data becomes viewed as an asset by consumers and privacy policies, laws, and regulations become more prominent, we risk throwing the baby out with the bathwater without a logical and efficient way to exchange data between businesses and consumers. Data licenses may provide a solution.

    11 min

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