Sat.Apr 30, 2022 - Fri.May 06, 2022

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Hypothesis Testing Explained

KDnuggets

This brief overview of the concept of Hypothesis Testing covers its classification in parametric and non-parametric tests, and when to use the most popular ones, including means, correlation, and distribution, in the case of one sample and two samples.

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Handling Missing Values with Random Forest

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction to Random Forest Missing values have always been a concern for any statistical analysis. They significantly reduce the study’s statistical powers, which may lead to faulty conclusions. Most of the algorithms used in statistical modellings such as Linear regression, Logistic Regression, […].

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Follow the latest AI trends to survive tomorrow

Dataconomy

Are you searching for the newest Artificial Intelligence Trends? In 2022, artificial intelligence will have progressed far enough to become the most revolutionary technology ever created by man. According to Google CEO Sundar Pichai, its impact on our evolution as a species will be comparable to fire and electricity. The.

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Why DBAs Must Automate to Survive

The Data Administration Newsletter

You might think the title of this article is some­what controversial, but you should wait until you’ve read to the end to render judgment. There are several important shifts impacting data management and database administration that cause manual practices and procedures to be ineffective. Let’s examine several of these trends. Data Growth But No DBA […].

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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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Machine Learning Is Not Like Your Brain Part One: Neurons Are Slow, Slow, Slow

KDnuggets

Artificial intelligence is not all that intelligent. While today’s AI can do some extraordinary things, the functionality underlying its accomplishments has very little to do with the way in which a human brain works to achieve the same tasks.

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Introduction to Image Segmentation

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction on Image Segmentation Suppose we have this image and the question that we are trying to solve is, what is the object present in this image. The object of importance here is the dog. Now, this looks like a simple enough problem, […]. The post Introduction to Image Segmentation appeared first on Analytics Vidhya.

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Machine Learning Helps Improve Tronc Management Considerably

Smart Data Collective

Did you know that around 37% of businesses use machine learning to some degree? This figure is growing significantly by the year. There are many reasons that more companies are turning to machine learning technology. One of the benefits of leveraging machine learning is that it can help with develop employee compensation schemes. Joanne Sammer, an author with Better Workplace Better World published an article on the use of AI in making pay decisions.

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SQL Notes for Professionals: The Free eBook Review

KDnuggets

The free book is a combination of SQL cheat sheets and practical database examples. It provided bite-size information about every SQL function and attribute with coding samples.

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The DataHour: Build Your First Chatbot Using Open Source Tools

Analytics Vidhya

Dear Readers, The latest edition of our flagship learning series on everything in and about data analytics is sure to excite your minds, be prepared for the DataHour on Building your First Chatbot using Open Source Tools. The session will be hosted by Dr. Rachael Tatman- Staff Developer Advocate at Rasa, the world’s leading conversational […].

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The basics of AI for beginners

Dataconomy

Today, we look at the basics of artificial intelligence, which permeates almost every aspect of our lives. This article will explore the main concepts revolving around artificial intelligence and the answers to frequently asked questions without getting into technical complexities as much as possible. What is artificial intelligence? Artificial intelligence.

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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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Seven Benefits of Using AI to Perform Text Analysis

Smart Data Collective

Artificial intelligence is often portrayed as a technology that will make robots rule over humans. No wonder many people fear that computers and other AI—enabled devices will control us. However, if we keep aside this dangerous depiction of AI, we can see how beneficial such systems are in our lives. Businesses are including more of it in their companies and adopting methods like AI text analysis. .

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6 Highest Paying Companies for Data Scientists

KDnuggets

These are the six top paying companies for data scientists. I’ve looked at absolute salary, but I’ll fill you in on other factors you should consider as well when it comes to picking a data science job for money.

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Know About Ensemble Methods in Machine Learning

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction The variance is the difference between the model and the ground truth value, whereas the error is the outcome of sensitivity to tiny perturbations in the training set. Excessive bias might cause an algorithm to miss unique relationships between the intended outputs and the […].

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A privacy-driven ecosystem for a sustainable data economy

Dataconomy

Data governance is a fundamental concept that must be addressed globally as data resources become increasingly essential in today’s world. However, there are several problems with data governance, including uneven data rights and conflicting interests between the players in the data economy. The regulations for how governments and businesses gather.

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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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Beef and the rainforest

FlowingData

People like beef. To raise more cattle, companies need more land. Sometimes to get more land, companies turn to unethical methods. Terrence McCoy and Júlia Ledur for The Washington Post : By reviewing thousands of shipment and purchase logs, and analyzing satellite imagery of Amazon cattle ranches, The Post found that JBS has yet to disentangle itself from ties to illegal deforestation.

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How To Structure a Data Science Project: A Step-by-Step Guide

KDnuggets

Check out all the necessary steps to successfully structure your data science projects leveraging data science templates.

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Getting Started with Azure Synapse Analytics

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Azure Synapse Analytics is a cloud-based service that combines the capabilities of enterprise data warehousing, big data, data integration, data visualization and dashboarding. Azure Synapse empowers numerous organizations in decision-making with the help of prescriptive and predictive analytics capabilities using its integration […].

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How to manage the machine learning lifecycle?

Dataconomy

What is the machine learning lifecycle represent? Automatically learning without being pre-programmed is possible thanks to machine learning. But what exactly is a machine learning system, and how does it work? So, it is classified as a machine learning life cycle. The machine learning life cycle is a cyclical process.

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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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What I Learned from Executing Data Quality Projects

The Data Administration Newsletter

Getting to great data quality need not be a blood sport! But there must be a method to the madness, and you need to be persistent and properly involve relevant stakeholders to achieve long lasting improvements. This article aims to provide some practical insights gained from enterprise master data quality projects undertaken within the past […].

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9 Free Harvard Courses to Learn Data Science in 2022

KDnuggets

Learn Python programming, statistics, and machine learning online from one of the world’s top universities.

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Approaching Classification With Neural Networks

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction on Classification Classification is one of the basic tasks that a machine can be trained to perform. This can include classifying whether it will rain or not today using the weather data, determining the expression of the person based on the facial […]. The post Approaching Classification With Neural Networks appeared first on Analytics Vidhya.

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AI drives the Industry 4.0 transformation

Dataconomy

Artificial Intelligence in Industry 4.0 enables companies to manufacture, enhance and distribute their products in revolutionized new ways. Welcome to the era of so-called dark factories! Manufacturers are integrating new technologies into their manufacturing facilities and operations, including artificial intelligence and its subdomain machine learning, as well as the Internet.

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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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Taking Their Time Series Talents to South Beach: How McLaren Is Gaining an Edge with Accurate Weather Data

DataRobot Blog

If you’ve ever driven through Texas or Florida during a rare Southern snowstorm, a few things quickly become cartoonishly obvious—your tyres matter, your driving matters, and your ability to navigate changing weather conditions really matters. As the Formula 1 Miami Grand Prix culminates on May 8, 2022, it’s not likely to be snowing. The forecast calls for sunny skies and temperatures between 68?

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How to Build Strong Data Science Portfolio as a Beginner

KDnuggets

After learning the basics of data science, you can start to work on real-world problems. But how do you showcase your work? In this article, we are going to learn a unique way to create a data science portfolio.

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The Ultimate Guide to Working With Mongo DB Using Python

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction on Mongo DB In the first part of this article, we will try to understand Mongo DB architecture along with how the Mongo DB database can be used for Data Science. We will first try to understand how is Mongo DB different […]. The post The Ultimate Guide to Working With Mongo DB Using Python appeared first on Analytics Vidhya.

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UK regulators are calling for views on algorithmic processing and auditing

Dataconomy

The UK’s digital watchdogs are seeking views on algorithmic processing and auditing, as well as areas of common interest between the organizations, in order to simplify and shape future cooperation. Benefits and harms of algorithmic processing are being discussed The Digital Regulation Cooperation Forum (DRCF) was formed in July 2020.

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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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7 Consequences of a Data Intrusion: Insights From Asiaciti Trust & MGM International

Smart Data Collective

Unauthorized data intrusions have been occuring with alarming frequency. From the highly sophisticated 2021 incident better known as the Pandora Papers to the massive hospitality breach that caused the personal details of millions of MGM hotel guests to be exposed on the dark web, such incidents are a distressing fact of modern life. It’s tempting to think of the risk of a data intrusion as an unavoidable cost of doing business.

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Image Classification with Convolutional Neural Networks (CNNs)

KDnuggets

In this article, we’ll look at what Convolutional Neural Networks are and how they work.

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Car Sales Demand Forecasting Using Pycaret

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction In this article, we will try to predict the car sales demand given the train and test data. This problem was introduced as a JOBATHON competition on the Analytics Vidhya platform which ran from 22 April 2022 to 24 April 2022. The data that we […]. The post Car Sales Demand Forecasting Using Pycaret appeared first on Analytics Vidhya.

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What is the future of healthcare data security?

Dataconomy

The healthcare industry, like many sectors, is undergoing a substantial data-driven transformation. New technologies like telehealth platforms and the internet of things (IoT) generate more granular medical data and make it more accessible. While this has many benefits, it also raises considerable healthcare data security concerns. There were 714 healthcare.

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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.