Sat.Aug 13, 2022 - Fri.Aug 19, 2022

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What Does ETL Have to Do with Machine Learning?

KDnuggets

ETL during the process of producing effective machine learning algorithms is found at the base - the foundation. Let’s go through the steps on how ETL is important to machine learning.

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Building a simple Flask App using Docker vs Code

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction More often than not, developers run into issues of an application running on one machine versus not running on another. Dockers help prevent this by ensuring the application runs on any machine if it works on yours. Simply put, if your job as […]. The post Building a simple Flask App using Docker vs Code appeared first on Analytics Vidhya.

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Visual explanations for machine learning

FlowingData

As part of a teaching initiative by Amazon, MLU-Explain is a series of interactive explainers on core machine learning concepts. Learn about training sets, decision trees, random forests, and more. Seems like a good way to spend a Friday night if you ask me. Tags: Amazon , machine learning.

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Why Is Data Loss Prevention is Crucial for Business?

Smart Data Collective

Data loss is a serious problem for many businesses. An estimated 94% do not survive a catastrophic data loss. Data loss prevention (DLP) strives to protect your business data from inside or outside compromise. This includes data leakage, data loss , misuse of data, or data compromised by unauthorized parties. DLP software aims to identify and classify crucial business data and pinpoint potential organization or policy packs violations.

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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have migrated their testing and production workloads to the cloud, yet development environments often remain tied to outdated local setups, limiting efficiency and growth.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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How Do Data Scientists and Data Engineers Work Together?

KDnuggets

If you’re considering a career in data science, it’s important to understand how these two fields differ, and which one might be more appropriate for someone with your skills and interests.

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The DataHour: Your Upcoming Learning Timeline

Analytics Vidhya

Dear Readers, Data Science is a vast subject, and the learning you can get is immense. And we at Analytics Vidhya always try to bring new learning topics and build up your skills. This time, we have not one, not two, but six new DataHour for you to attend. So, keep your notepad handy and […]. The post The DataHour: Your Upcoming Learning Timeline appeared first on Analytics Vidhya.

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5 Ways Companies Use Machine Learning to Improve Workplace Productivity

Smart Data Collective

Technology has become so advanced that, today, there’s an app for almost anything, from children’s education, to home improvement, to health monitoring, to workplace productivity. Gathering critical data to determine the best action to apply to specific situations has become integral in people’s daily lives. Because of technology, critical decisions are now mostly based on scientific data.

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Why is Data Management so Important to Data Science?

KDnuggets

High data availability may help power digital transformation, but data management systems are needed to keep that data organizaed and make it accessible. Read this article to see why data management is important to data science.

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AWS Glue for Handling Metadata

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction AWS Glue helps Data Engineers to prepare data for other data consumers through the Extract, Transform & Load (ETL) Process. The managed service offers a simple and cost-effective method of categorizing and managing big data in an enterprise. It provides organizations with […].

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Worst drought in Europe, in 500 years

FlowingData

Dominic RoyĂ© mapped river discharge in Europe over the past few months: A single map for the worst #drought in 500 years in Europe. The river discharge anomaly based on reanalysis data from June to August 12 2022, shows an average negative anomaly of -29%, even reaching less than -62% at some points. #rstats #dataviz pic.twitter.com/LSGMfS52Lm. — Dr.

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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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Can ML Fix Cybersecurity Challenges in Healthcare?

Smart Data Collective

The Department of Health and Human Services HIPAA Breach Reporting Tool shows that there were over 700 data breaches in healthcare organizations last year. Healthcare organizations need to utilize the latest technology to stop these attacks. Machine learning technology is especially important. Machine Learning Helps Healthcare Organizations Fight Cyberattacks.

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Machine Learning Over Encrypted Data

KDnuggets

This blog outlines a solution to the Kaggle Titanic challenge that employs Privacy-Preserving Machine Learning (PPML) using the Concrete-ML open-source toolkit.

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Image Contrast Enhancement Using CLAHE

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Contrast enhancement algorithms have evolved over the last few decades to meet the needs of its objectives. There are two main goals in enhancing an image’s contrast: (i) Improving its appearance for visual interpretation and (ii) facilitating/increasing the performance of subsequent tasks […].

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AI in Supply Chain — A Trillion Dollar Opportunity

DataRobot Blog

Supply chain and logistics industries worldwide lose over $1 trillion a year due to out-of-stock or overstocked items 1. Shifting demands and shipping difficulties make the situation worse. Challenges in inventory management, demand forecasting, price optimization, and more can result in missed opportunities and lost revenue. The retail marketplace has become increasingly complex and competitive.

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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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Hybrid Vs. Multi-Cloud: 5 Key Comparisons in Kafka Architectures

Smart Data Collective

Cloud technology is becoming more important to modern businesses than ever. Ninety-four percent of enterprises invest in cloud infrastructures, due to the benefits it offers. An estimated 87% of companies using the cloud rely on hybrid cloud environments. However, some companies use other cloud solutions, which need to be discussed as well. These days, most companies’ cloud ecosystem includes infrastructure, compliance, security, and other aspects.

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How to Use Data Visualization to Add Impact to Your Work Reports and Presentations

KDnuggets

For anyone whose work involves presenting data, understanding the art and science of data visualization — and its emphasis on storytelling — can make or break your ability to communicate key insights.

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What is Apache Impala- Features and Architecture

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Impala is an open-source and native analytics database for Hadoop. Vendors such as Cloudera, Oracle, MapReduce, and Amazon have shipped Impala. If you want to learn all things Impala, you’ve come to the right place. source: -[link] It rapidly processes large […].

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Data Speaks for Itself: What Could Possibly Go Wrong?

The Data Administration Newsletter

I had a great experience attending the MIT Chief Data Officer and Information Quality Symposium in Cambridge this July. It was truly enlightening to hear from so many experienced data leaders. This year, there were 2,855 registered attendees from 63 countries, including 1,218 Chief Data Officers. I always learn so much at these symposia. In […].

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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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Key Reasons Businesses Are Embracing AI

Smart Data Collective

Businesses are evolving and searching for newer ways to accomplish their goals, hence the need for artificial intelligence (AI). AI involves building smart machines to carry out tasks that typically need human intelligence, and AI simulates human intelligence using computer systems. The two major AI types used in businesses today are reactive machines and limited memory.

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The Data Quality Hierarchy of Needs

KDnuggets

Just as Maslow identified a hierarchy of needs for people, data teams have a hierarchy of needs, beginning with data freshness; including volumes, schemas, and values; and culminating with lineage.

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Basic Introduction to Data Science Pipeline

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction The Data science pipeline is the procedure and equipment used to compile raw data from many sources, evaluate it, and display the findings in a clear and concise manner. Businesses use the method to get answers to certain business queries and produce […]. The post Basic Introduction to Data Science Pipeline appeared first on Analytics Vidhya.

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Data Governance Keys to Success

The Data Administration Newsletter

Unfortunately, a lot of data governance programs fail and there are many reasons why. The silver lining is that there are great lessons from these failures that we can learn from and make sure that we will avoid them in our data governance program. Here are the keys to data governance success: Treat Data Governance as […].

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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.

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Why the Consumable Form of Data Needs Your Attention

Dataversity

How organizations manage their data directly impacts their success or failure. The correlation between data analytics and intelligence to competitive advantage and growth has led to heavy investments in those technologies throughout the last decade. So, if you consider that content is the consumable form of data, then it follows that the era of big […].

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The Complete Collection of Data Science Projects – Part 2

KDnuggets

The second part covers the list of Machine Learning, Deep Learning, Computer Vision, Natural Language Processing, Data Engineering, and MLOps.

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Database Normalization- A Step-by-Step Guide with Examples

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction As an SQL Developer, you regularly work with enormous amounts of data stored in different tables that are present inside databases. This often becomes difficult to extract the information if it is not organized properly. We can solve this problem using Normalization by […].

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Tracked while reading about being tracked at work

FlowingData

While reading this NYT article, by Jodi Kantor and Arya Sundaram, on the drawbacks of activity and time tracking for work, the article itself tracks your reading behavior. You see counters for the time you spend reading and scrolling, clicks, keystrokes, idle time, and active time. It comes complete with snippy comments and a final grade — and a bitter taste for productivity tracking.

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How to Drive Cost Savings, Efficiency Gains, and Sustainability Wins with MES

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.

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A Primer to Optimizing Your Apache Cassandra Compaction Strategy

Dataversity

When setting up an Apache Cassandra table schema and anticipating how you’ll use the table, it’s a best practice to simultaneously formulate a thoughtful compaction strategy. While a Cassandra table’s compaction strategy can be adjusted after its creation, doing so invites costly cluster performance penalties because Cassandra will need to rewrite all of that table’s data.

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Is There a Way to Bridge the MLOps Tools Gap?

KDnuggets

Converting Jupyter notebooks to a well-designed software system is a mandatory step in every ML project. But there is a notable lack of tooling to assist developers with such translation, beyond the basic nbconvert utility.

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Dealing with outliers using the Z-Score method

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Outlier detection is one of the widely used methods in any data science project, as its presence can lead to the development of a bad machine learning model. Let’s take a quick scenario of the linear regression problem statement, where suppose you […]. The post Dealing with outliers using the Z-Score method appeared first on Analytics Vidhya.

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Simplicity is An Advantage but Sadly Complexity Sells Better

Eugene Yan

Pushing back on the cult of complexity.

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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.