Sat.Jun 18, 2022 - Fri.Jun 24, 2022

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Most Frequently Asked Google Big Query Interview Questions

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Big Query is a serverless enterprise data warehouse service fully managed by Google. Big Query provides nearly real-time analytics of massive data. A big Query data warehouse provides global availability of data, can be easily connected to the other Google Services and […].

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20 Basic Linux Commands for Data Science Beginners

KDnuggets

Essential Linux commands to improve the data science workflow. It will give you the power to automate tasks, build pipelines, access file systems, and enhance development operations.

professionals

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This self-driving car remembers the past using neural networks

Dataconomy

Researchers at Cornell University have developed a technique to assist self-driving cars in recalling past events and utilize them as references while navigating, especially in bad weather when the vehicle’s sensors cannot be trusted. On cars, normally, artificial neural networks are not concerned with memory from the past, and they.

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AI Helps Mitigate These 5 Major Supplier Risks

Smart Data Collective

Artificial intelligence is driving a lot of changes in modern business. Companies are using AI to better understand their customers, recognize ways to manage finances more efficiently and tackle other issues. Since AI has proven to be so valuable, an estimated 37% of companies report using it. The actual number could be higher, since some companies don’t realize the different forms of AI they might be using.

AI 130
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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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Multi-Table Analysis with MYSQL

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction on MYSQL In this article, we will see how to work with multiple tables. Learning SQL is very important nowadays. It is a very popular technology that most companies are using. SQL queries are used for querying tables in the process of data analysis. […]. The post Multi-Table Analysis with MYSQL appeared first on Analytics Vidhya.

SQL 375
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Introducing Objectiv: Open-source product analytics infrastructure

KDnuggets

Collect validated user behavior data that’s ready to model on without prepwork. Take models built on one dataset and deploy & run them on another.

Analytics 400

More Trending

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Using Data Analytics and QR Codes to Boost Your Marketing Strategy

Smart Data Collective

Data analytics technology has helped countless companies improve their marketing strategies. Global companies are spending over $3 billion a year on marketing analytics technology and this figure is growing over 12% a year. There are a lot of different ways that companies can use data analytics to improve their marketing strategies. One of the most effective approaches involves taking advantage of QR codes.

Analytics 129
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Understanding Loss Function in Deep Learning

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction The loss function is very important in machine learning or deep learning. let’s say you are working on any problem and you have trained a machine learning model on the dataset and are ready to put it in front of your client. […]. The post Understanding Loss Function in Deep Learning appeared first on Analytics Vidhya.

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Super Study Guide: A Free Algorithms and Data Structures eBook

KDnuggets

Check out Super Study Guide: Algorithms and Data Structures, a free ebook covering foundations, data structures, graphs, and trees, sorting and searching.

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The quantum boost to AI paves the way for AGI

Dataconomy

Quantum artificial intelligence is here to pave the way for the next chapter of our digital intellect pursuit. Artificial intelligence is a transformative technology, and it needs quantum computing to achieve significant improvement. Although artificial intelligence may be used with conventional computers, it is restricted by conventional computational capabilities.

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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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Migrating to the cloud? Follow these steps to encourage success

Smart Data Collective

Enterprise cloud adoption increased dramatically during the COVID-19 pandemic — now, it’s the rule rather than the exception. In fact, 9 in 10 companies currently use the cloud in some capacity, according to a recent report from O’Reilly. Although digital transformation initiatives were already well underway in many industries, the global health crisis introduced two new factors that forced almost all organisations to move operations online.

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Top 10 Web 3.0 Technologies that will Shape our Future World

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction The internet has come a long way since Web 1.0. Hypertext Markup Language (HTML) defines the layout and delivery of websites in Web 1.0 and Web 2.0 technologies. With Web 3.0, HTML will remain a core layer, but how it connects to […]. The post Top 10 Web 3.0 Technologies that will Shape our Future World appeared first on Analytics Vidhya.

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Tech visionaries to address accelerating machine learning, unifying AI platforms and more at the AI Hardware Summit & Edge AI Summit

KDnuggets

Tech visionaries to address accelerating machine learning, unifying AI platforms and taking intelligence to the edge, at the fifth annual AI Hardware Summit & Edge AI Summit, Santa Clara.

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Is HR ready for blockchain?

Dataconomy

The demand for blockchain in HR is increasing, and we are here to explain why. Blockchain technology is quickly becoming a staple in many industries, including HR. Here are some of the advantages of using blockchain in HR, as well as examples of startups that are already using it. Blockchain.

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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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Automotive Industry Uses Analytics To Solve Pressing Supply Chain Issues

Smart Data Collective

The automotive industry is struggling to meet demand as a growing supply chain shortage cripples the global economy. Chip shortages, among other components, have fueled a steep increase in car prices, as much as USD$900 above the manufacturer-suggested retail price (MSRP) for non-luxury cars and USD$1,300 above MSRP for luxury ones. . Market analysts predict the supply chain to normalize in the third quarter of 2022, which is only a few months away as of this publication.

Analytics 119
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Is Adult Income Dataset Imbalanced?

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. [link] Introduction How many rows of sample data are required (or what should be the size of the training dataset required) to build a machine learning model that can predict fraudulent transactions in a credit card fraud detection dataset containing around 284407 rows? […]. The post Is Adult Income Dataset Imbalanced?

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Market Data and News: A Time Series Analysis

KDnuggets

In this article we introduce a few tools and techniques for studying relationships between the stock market and the news. We explore time series processing, anomaly detection, and an event-based view of the news. We also generate intuitive charts to demonstrate some of these concepts, and share the code behind all of this in a notebook.

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Quantum computing turns into accessible services with the cloud-based quantum computers

Dataconomy

Quantum cloud computing is a field that emerged with the convergence of quantum computing and cloud computing, two of the most influential technologies of our time. In the simplest terms, quantum cloud computing enables quantum computing resources to be available over the cloud. Quantum computers compute differently, allowing them to.

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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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How Credit Providers and Lenders Use Data Effectively

Smart Data Collective

Big data technology has had massive implications for the financial industry. Banks, credit card companies and other financial service providers are leveraging big data in unprecedented ways. One of the biggest benefits of big data is with loan and mortgage processing. The use of data can be crucial for credit card companies and those offering loans and mortgages.

Big Data 115
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Data Science in Web 3.0

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction on Web 3.0 As a result of centralization, the Internet has been able to serve billions of users and build a solid foundation upon which it can continue to thrive. At the same time, the World Wide Web is controlled by a few […]. The post Data Science in Web 3.0 appeared first on Analytics Vidhya.

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Top Posts June 13-19: 14 Essential Git Commands for Data Scientists

KDnuggets

Also: Decision Tree Algorithm, Explained; 15 Python Coding Interview Questions You Must Know For Data Science; Naïve Bayes Algorithm: Everything You Need to Know; Primary Supervised Learning Algorithms Used in Machine Learning.

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Show your musical taste with data: The best analytics tools for Spotify

Dataconomy

Spotify analytics for listeners is how the popular streaming service also captures the hearts of its users. Many websites allow you to check these analytics if you have ever wanted to delve deeper into your listening habits — maybe to see which songs you listen to the most or compare.

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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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? Visually Inefficient

FlowingData

Welcome to issue #194 of The Process , the newsletter for FlowingData members that looks closer at how the charts get made. I’m Nathan Yau, and this week I’m trading optimized visual efficiency for joy and interest. Become a member for access to this — plus tutorials, courses, and guides.

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Differences Between Web 2.0 and Web 3.0

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction If you have been paying close attention to the blockchain industry, then you have undoubtedly been familiar with the words “Web 2.0” and “Web 3.0.” There’s a good chance that you’re confused about the precise meaning of these phrases and how they […].

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Data Science Career: 7 Expectations vs Reality

KDnuggets

Let’s get into some of the expectations of data scientists – and the reality they face.

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The most comprehensive blockchain glossary in 2022

Dataconomy

The blockchain glossary we have prepared also includes the highlights of the web3 glossary and NFT glossary of terms. Blockchain terminology is expanding daily with the increasing popularity of blockchain technology. It isn’t easy to keep up with all of it. Rather than cryptocurrencies, there are several blockchain use cases, such.

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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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5 Huge Benefits of Financial Analytics for Your Business

Smart Data Collective

Data analytics technology has become a pillar in modern business. A growing number of companies are utilizing data analytics to improve their operating strategies. One of the most important functions that data analytics is helping with is finance. Companies are projected to spend just shy of $20 billion on financial analytics services in 2030. Are youu wondering how your company can benefit from financial analytics ?

Analytics 103
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Which is better? Bitcoin Vs Ethereum

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction In this article, we will see the two main cryptocurrencies, Bitcoin and Ethereum. Let us learn about them. What differences do they have and which coin is best for investment and what makes that particular coin better. Nowadays cryptocurrencies are quite popular. […].

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Machine Learning Is Not Like Your Brain Part 4: The Neuron’s Limited Ability to Represent Precise Values

KDnuggets

In the fourth installment, we focus on a fundamental issue: it is difficult to represent numerical values in neurons and impractical to represent them with precision.

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A new ML method will be the driving force toward improving algorithms

Dataconomy

Algorithms with predictions is a new approach that takes advantage of data insights that machine learning technology may provide into data that conventional methods may not handle. Algorithms are the basic tools of modern computing. Algorithms are the machinery inside a watch, executing pre-defined operations within more complex programs. Their.

Algorithm 198
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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.