Mon.Apr 04, 2022

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erwin® Data Modeler by Quest® R12.0: Leading the way with a new DevOps GitHub capability

erwin

If you’re a long-time erwin ® Data Modeler by Quest ® customer, you might be asking yourself, “What happened to the release naming convention of erwin Data Modeler?” In 2021 erwin Data Modeler released 2021R1. But in 2022, the release naming convention changed from following the standard practice using the current year and number of releases to R12.

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Innovative Applications of Machine Learning in Healthcare Domain

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Nowadays, Machine learning is being used in various areas in the health business, including the development of improved medical processes, the management of patient records and data, and the treatment of chronic diseases. Healthcare firms may use machine learning to meet rising demand, […].

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The Complete Collection Of Data Repositories – Part 1

KDnuggets

Check out the collection of the best data repositories on agriculture, audio, biology, climate, computer vision, economics, education, energy, finance, and government.

Finance 146
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Building Vehicle Counter System Using OpenCV

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction In this article, we are going to build a vehicle counter system using OpenCV in Python using the concept of Euclidean distance tracking and contours. In the last article, we talked about object detection in OpenCV using haar cascades, if you haven’t […]. The post Building Vehicle Counter System Using OpenCV appeared first on Analytics Vidhya.

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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.

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The pandemic pivot: 5 key leadership lessons that will last

CIO Business Intelligence

Two years after a global pandemic first shut down the world — and IT departments took a leading role in maintaining businesses’ survival — the IT function has been changed forever. As the dust has settled, many tech leaders have found that changes they were forced to make to their work strategies, leadership styles, and team structures have turned out to be team-transforming epiphanies that will endure going forward.

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Ways to Calculate Hashing in Data Structure

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Hashing is the process of mapping keys and values into a hash table by using a hash function. It makes elements more accessible faster. The efficiency of the hash function determines how well it can handle the mapping. When you have 20000 […]. The post Ways to Calculate Hashing in Data Structure appeared first on Analytics Vidhya.

More Trending

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Predicting House Prices Using Keras Functional API

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction The Keras Functional API is a way of creating models that are more flexible and complex than the traditional sequential model. The functional API can handle models with non-linear topology, shared layers, and even multiple inputs or outputs. On the contrary, The sequential API allows […].

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How to Bring Presentation Data to Life with Powered Template

Smart Data Collective

We have talked in the past about the importance of data visualization in business. One study by Robert Horn at Stanford found that 64% of participants made a decision immediately after watching a presentation with an overview map. However, many companies are struggling to figure out how to use data visualization effectively. One of the ways to accomplish this is with presentation templates that can use data modeling.

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Principal Component Analysis & its Implementions

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. In Machine Learning problems, teams deal with a lot of data. Not all data is useful and can be utilized. Usually, some data has to be left out of the training process so that only the most relevant data and features are used. This […]. The post Principal Component Analysis & its Implementions appeared first on Analytics Vidhya.

IT 304
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Logistic Regression for Classification

KDnuggets

Deep dive into Logistic Regression with practical examples.

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Peak Performance: Continuous Testing & Evaluation of LLM-Based Applications

Speaker: Aarushi Kansal, AI Leader & Author and Tony Karrer, Founder & CTO at Aggregage

Software leaders who are building applications based on Large Language Models (LLMs) often find it a challenge to achieve reliability. It’s no surprise given the non-deterministic nature of LLMs. To effectively create reliable LLM-based (often with RAG) applications, extensive testing and evaluation processes are crucial. This often ends up involving meticulous adjustments to prompts.

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An Introduction to RNN for Beginners

Analytics Vidhya

Introduction Have you ever used “Grammarly” or “text summarizer” and wondered how does Grammarly tells us grammatical mistakes or how “Apple’s Siri” and “Amazon Alexa” understand what you say? There is an interesting algorithm working behind all these applications named “Recurrent Neural Networks” or RNN in short. The first time I came across RNNs, I […].

Analytics 271
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Clean Harbors’ CIO: Hybrid approach to the cloud is a win-win

CIO Business Intelligence

For many organizations, the recent rush to the cloud has also given pause to strategic considerations around what best to leave in house. Clean Harbors is one such entity taking a hybrid approach to its digital transformation to ensure high availability of key systems while still gaining access to advanced AI and automation capabilities where necessary in the cloud.

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Flat vs Hierarchical clustering: Book Recommendation System

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Overview Clustering is an unsupervised machine learning algorithm that basically groups similar things together. Recommendation Engines is a fundamental application of clustering. We will build a Collaborative filtering Book recommendation system and compare flat vs hierarchical clustering; which works better?

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Securing Your Cloud Supply Chain

CIO Business Intelligence

By Matt Chiodi, Chief Security Officer, Public Cloud, Palo Alto Networks. Supply chain security has become top-of-mind for many leaders, as incident after incident has revealed supply chain vulnerabilities that expose significant organizational risk. Security challenges like Log4j and SolarStorm have battered organizations of all sizes with risks they likely didn’t even know they had.

Risk 114
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The Path to Product Excellence: Avoiding Common Pitfalls and Enhancing Communication

Speaker: David Bard, Principal at VP Product Coaching

In the fast-paced world of digital innovation, success is often accompanied by a multitude of challenges - like the pitfalls lurking at every turn, threatening to derail the most promising projects. But fret not, this webinar is your key to effective product development! Join us for an enlightening session to empower you to lead your team to greater heights.

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Know all About 2D and 3D Pose Estimation!

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Let’s find out how to use pose estimation for such Snapchat filters, shall we? Have you ever wondered how Snapchat uses its filters and engages people so much? The filters on Snapchat are of various kinds, from funny to using makeup filters […]. The post Know all About 2D and 3D Pose Estimation!

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How to Avoid Death by PowerPoint by Differentiating Between Slidedocs and Slidedecks

Depict Data Studio

Do you use PowerPoint? Probably. What do you use PowerPoint for? You might use PowerPoint to: Create slides to accompany a presentation (i.e., you’re getting ready to speak at a conference, meeting, or other in-person or virtual event); and/or Create documents that someone can read on their own (i.e., when you’ll circulate the slides as an email attachment before or after a meeting).

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A Simple Data Pipeline to Show Use of Python Iterator

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction In this blog, we will explore one interesting aspect of the pandas read_csv function, the Python Iterator parameter, which can be used to read relatively large input data. Pandas library in python is an excellent choice for reading and manipulating data as data frames. […].

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Microsoft to optimize process automation stack with Minit acquisition

CIO Business Intelligence

Microsoft has bought Minit, a developer of process mining software, to help its customers optimize business processes across the enterprise, on and off Microsoft Power Platform. The move came just days after Celonis announced its purchase of Process Analytics Factory to boost its own process mining offering on Microsoft Power Platform — and in the same week that SAP unveiled new functionality for Signavio , the process mining tool it acquired barely a year earlier, pulling together data on proce

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How to Build an Experimentation Culture for Data-Driven Product Development

Speaker: Margaret-Ann Seger, Head of Product, Statsig

Experimentation is often seen as an aspirational practice, especially at smaller, fast-moving companies who are strapped for time and resources. So, how can you get your team making decisions in a more data-driven way while continuing to remain lean and maintaining ship velocity? In this webinar, Margaret-Ann Seger, Head of Product at Statsig, will teach you how to build an experimentation culture from the ground-up, graduating from just getting started with data-driven development to operating

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Gain Customer’s Confidence in ML Model Predictions

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction One of the key challenges in Machine Learning Model is the explainability of the ML Model that we are building. In general, ML Model is a Black Box. As Data scientists, we may understand the algorithm & statistical methods used behind the scene. […]. The post Gain Customer’s Confidence in ML Model Predictions appeared first on Analytics Vidhya.

Modeling 289
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Why Can’t we Advance Healthcare and Life Sciences this Fast all the time?

Cloudera

Vaccine development became the top priority for the life sciences industry – delivering new vaccines at unprecedented speed and maneuvering large-scale production processes. Numerous factors helped accelerate the vaccine roll-out including prior research, genome sequencing, jumping the FDA approval queue and a plethora of testing volunteers. So now that we’ve experienced these advancements, how can the industry keep momentum to speed-up innovative solutions across healthcare?

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Complete Flow of Decision Tree Algorithm

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction In Machine Learning, there are two types of algorithms. One is Supervised, and the other is Unsupervised algorithms. A decision tree algorithm is a supervised Machine Learning Algorithm. There are many algorithms in supervised Machine Learning Algorithms like Random Forest, K-nearest neighbour, Naive […].

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Making Cyber Resiliency a Priority in Healthcare: My Advice for Leaders

CIO Business Intelligence

By Derrick Lowe, Chief Information Security Officer at Orlando Health, a Palo Alto Networks customer. When I talk to healthcare industry leaders about cyber resiliency, I get a lot of affirmative head-nodding and positive feedback. And why not? Healthcare resiliency, in general, and in cybersecurity particularly, is a concept that is easy to get behind.

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Reimagined: Building Products with Generative AI

“Reimagined: Building Products with Generative AI” is an extensive guide for integrating generative AI into product strategy and careers featuring over 150 real-world examples, 30 case studies, and 20+ frameworks, and endorsed by over 20 leading AI and product executives, inventors, entrepreneurs, and researchers.

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A Comprehensive Guide to Sharding in Data Engineering for Beginners

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Big Data is a very commonly heard term these days. A reasonably large volume of data that cannot be handled on a small capacity configuration of servers can be called ‘Big Data’ in that particular context. In today’s competitive world, every business […]. The post A Comprehensive Guide to Sharding in Data Engineering for Beginners appeared first on Analytics Vidhya.

Big Data 288
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Smarten Support Portal Updates – March – 2022!

Smarten

We invite you to explore our latest knowledgebase articles and to join the Smarten user community on Smarten Support Portal. If you have not registered yet, Click Here to obtain your login credentials. Knowledgebase Articles. SSDP : Convert timestamp based text formats to Timestamp. SSDP : Create dataset/cube using stored procedures in RDBMS. SSDP : Apply rounding logic to Time data.

Testing 62
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Beginners Guide on Apache Spark & RDDs

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction An ultimate beginners guide on Apache Spark & RDDs! As we all have observed, the growth of data how helps the companies to get insights into data, and that insight is used for the growth of Business. Personal assistants like Alexa, Siri, […]. The post Beginners Guide on Apache Spark & RDDs appeared first on Analytics Vidhya.

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Preventing Next-Generation Fraud with Graph Database Technology

CIO Business Intelligence

Annual losses from cybercrime worldwide are estimated to reach $10.5 trillion by 2025. These losses impact everyone from financial institutions, to businesses and individuals — victims of fraud. Part of the problem arises from the fact that many accounts rely on little more than a username and password to protect access, simplifying account takeover and identify theft.

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Entity Resolution Checklist: What to Consider When Evaluating Options

Are you trying to decide which entity resolution capabilities you need? It can be confusing to determine which features are most important for your project. And sometimes key features are overlooked. Get the Entity Resolution Evaluation Checklist to make sure you’ve thought of everything to make your project a success! The list was created by Senzing’s team of leading entity resolution experts, based on their real-world experience.

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EDA: Exploring the Unexplored!

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction The data being handled all around the world is just huge. We cannot even imagine how much data is being handled, processed, and used in various industries and companies. To get a better understanding of the data, one must learn how to do […]. The post EDA: Exploring the Unexplored!

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Data Lineage Examples for Healthcare Companies

Octopai

Have you taken the Hippocratic Oath? If you’re a physician, possibly. (Although it’s more likely you’ve taken one of the modern versions than Hippocrates’ original.). If you have any other role in the healthcare industry – from nurse to administrator, from clinical researcher to pharmaceutical developer – the Hippocratic Oath is more of a curiosity than a commitment.

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A Comprehensive Guide On Pygal – The Next Generation Data Visualization Library In Python

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. We have worked on different data visualization libraries over the last decade. Data visualization is the way to tell stories by curating data into a more simple plot and helps us understand and highlight the key trends in our data. Introduction A sound data […]. The post A Comprehensive Guide On Pygal – The Next Generation Data Visualization Library In Python appeared first on Analytics Vidhya.

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Bringing MMM to 21st Century with Machine Learning and Automation?

DataRobot Blog

What is MMM? MMM stands for Marketing Mix Model and it is one of the oldest and most well-established techniques to measure the sales impact of marketing activity statistically. MMM allows you to isolate incremental sales contributions coming from each of the marketing channels. When this contribution is put against the marketing spend in the particular channel, it produces a reading on the highly coveted return on investment (ROI).

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The Big Payoff of Application Analytics

Outdated or absent analytics won’t cut it in today’s data-driven applications – not for your end users, your development team, or your business. That’s what drove the five companies in this e-book to change their approach to analytics. Download this e-book to learn about the unique problems each company faced and how they achieved huge returns beyond expectation by embedding analytics into applications.