Sat.Nov 20, 2021 - Fri.Nov 26, 2021

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Most Common SQL Mistakes on Data Science Interviews

KDnuggets

Sure, we all make mistakes -- which can be a bit more painful when we are trying to get hired -- so check out these typical errors applicants make while answering SQL questions during data science interviews.

SQL 399
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Performing Time Series Analysis using ARIMA Model in R

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Welcome to the World of Time Series Analysis! From this article, you will learn how to perform time series analysis using the ARIMA model (with code!). The dataset used in this article can be downloaded here. The usage time series data consist of the […]. The post Performing Time Series Analysis using ARIMA Model in R appeared first on Analytics Vidhya.

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AI will soon oversee its own data management

Dataconomy

AI thrives on data. The more data it can access, and the more accurate and contextual that data is, the better the results will be. The problem is that the data volumes currently being generated by the global digital footprint are so vast that it would take literally millions, if not.

AI 253
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How to Utilize Artificial Intelligence in Your eCommerce SEO Strategy

Smart Data Collective

If you have not lived under a rock for several years, you have undoubtedly heard about artificial intelligence (AI). However, how might artificial intelligence be used in e-commerce operations? Artificial intelligence (AI) is starting to fill every facet of our daily lives. For example, self-checkout cash registers, airport security checks, and other automated processes all use artificial intelligence to some degree.

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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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Top Stories, Nov 15-21: 19 Data Science Project Ideas for Beginners

KDnuggets

Also: How I Redesigned over 100 ETL into ELT Data Pipelines; Where NLP is heading; Don’t Waste Time Building Your Data Science Network; Data Scientists: How to Sell Your Project and Yourself.

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Using Data Visualization to Explore the Human Space Race!

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Humankind has always looked up to the stars. Since the dawn of civilization, we have mapped constellations, named planets after Gods and so on. We have seen signs and visions in celestial bodies. In the previous century, we finally had the technology to […]. The post Using Data Visualization to Explore the Human Space Race!

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How BI Can Help Enterprises Overcome The Effects Of The Pandemic

Smart Data Collective

It’s been almost two years since the COVID-19 pandemic started, and now we have enough information to assume that most enterprises weren’t prepared for the crisis. Although teams had vast amounts of data and powerful analytic tools at their fingertips, the pandemic still caught most organizations off guard. As a result, most enterprise executives had to cut their plans and initiatives.

Analytics 126
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Top 4 Data Integration Tools for Modern Enterprises

KDnuggets

Maintaining a centralized data repository can simplify your business intelligence initiatives. Here are four data integration tools that can make data more valuable for modern enterprises.

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Understanding K-means Clustering in Machine Learning(With Examples)

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction With the rising use of the Internet in today’s society, the quantity of data created is incomprehensibly huge. Even though the nature of individual data is straightforward, the sheer amount of data to be analyzed makes processing difficult for even computers. To […].

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A Beginner’s Guide to AI and Machine Learning in Web Scraping

Dataversity

With uses spanning personalized medicine to the creation of social media clickbait, the use of artificial intelligence (AI) and machine learning (ML) is expected to transform industries from health care to manufacturing. Web scraping is no exception – and while its use is definitely not the answer to every data collection challenge, simple applications of AI/ML can enhance the process and increase […].

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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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How to Make the Most of Big Data in the Fitness Industry

Smart Data Collective

Big data has been a powerful force of change in the fitness industry. More fitness companies are using data analytics, AI and other technology to better understand their customers, improve their operating margins and make other changes to adapt to new trends. If you are running a fitness business, then you can’t afford to overlook the importance of big data.

Big Data 124
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On-Device Deep Learning: PyTorch Mobile and TensorFlow Lite

KDnuggets

PyTorch and TensorFlow are the two leading AI/ML Frameworks. In this article, we take a look at their on-device counterparts PyTorch Mobile and TensorFlow Lite and examine them more deeply from the perspective of someone who wishes to develop and deploy models for use on mobile platforms.

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Loan Risk Analysis with Supervised Machine Learning Classification

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction to Classification Algorithms In this article, we shall analyze loan risk using 2 different supervised learning classification algorithms. These algorithms are decision trees and random forests. At the outset, the basic features and the concepts involved would be discussed followed by a […].

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Email AI and Workflow Automation Saves Time and Money for Health Care

Dataversity

The current state of the labor market is imposing obstacles for employers across many industries to fill open positions – health care being chief of them. The global shortage of health care workers has forced practitioners into undertaking additional duties such as manual data entry alongside their general patient care duties. When practitioners shift their time […].

AI 98
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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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5 Ways Data Analytics Sets a New Standard for Revenue Marketing

Smart Data Collective

With the “big data” or insurmountable, high-volume amount of information, data analytics plays a crucial role in many business aspects, including revenue marketing. Data analytics refers to the systematic computational analysis of statistics or data. It lays a core foundation necessary for business planning. Data analytics make up the relevant key performance indicators ( KPIs ) or metrics necessary for a business to create various sales and marketing strategies.

Analytics 109
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Accelerating AI with MLOps

KDnuggets

Companies are racing to use AI, but despite its vast potential, most AI projects fail. Examining and resolving operational issues upfront can help AI initiatives reach their full potential.

AI 373
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Building an end-to-end Polynomial Regression Model in R

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Overview. Regression analysis is used to solve problems of prediction based on data statistical parameters. In this article, we will look at the use of a polynomial regression model on a simple example using real statistic data. We will analyze the relationship between […]. The post Building an end-to-end Polynomial Regression Model in R appeared first on Analytics Vidhya.

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Does AI Decision-Making Drive Your Business?

DataRobot

It should. By the year 2030, AI will deliver economic growth of $15.7 trillion, according to PwC Research. Does your business need: To target its customers more precisely? Reduce its operational costs? Develop exciting new products? Increase the reliability of its supply chain? Whatever its requirements, applying data-driven AI strategies can help. Let’s look at some examples to see how AI applications can aid any organization, large or small. .

AI 98
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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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Benefits of Using Data Analytics in Equipment Financing

Smart Data Collective

Data analytics technology has touched on virtually every element of our lives. More companies are using big data to address some of their biggest concerns. Securing financing is a huge example. Data analytics technology is helping more companies get the financing that they need for a variety of purposes. One of the most important benefits of big data involves getting financing for new equipment.

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Dask DataFrame is not Pandas

KDnuggets

This article is the second article of an ongoing series on using Dask in practice. Each article in this series will be simple enough for beginners, but provide useful tips for real work. The next article in the series is about parallelizing for loops, and other embarrassingly parallel operations with dask.delayed.

Python 368
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Getting Started with Data Analysis using Power BI

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. What is Power BI? Microsoft‘s business analytics product, Power BI, delivers interactive data visualization BI capabilities that allow users to see and share data and insights throughout their organisation. Power BI provides insight data by using data interactively and exploring it by visualizations. […].

Power BI 384
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Most Common Daily Schedules for Different Groups

FlowingData

We all have our routines, but from person-to-person, the daily schedule changes a lot depending on your responsibilities. Read More.

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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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Data Privacy and Internet Safety Tips for College Students

Smart Data Collective

Data privacy concerns have become greater than ever in recent years. One recent study from the University of Maryland found that there is a data breach every 39 seconds. The threat of data breaches has become a lot greater in recent years as more businesses and consumers become dependent on big data. The proliferation of big data has made digital privacy concerns much more significant.

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A Spreadsheet that Generates Python: The Mito JupyterLab Extension

KDnuggets

You can call Mito into your Jupyter Environment and each edit you make will generate the equivalent Python in the code cell below.

Python 364
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KNIME Tutorial – A Friendly Introduction to Components using the KNIME Analytics Platform

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. In the last article A Friendly Introduction to KNIME Analytics Platform I provided a brief insight into the open-source software KNIME Analytics Platform and what it is capable of. With the help of a customer segmentation example, I showed the general functions of […]. The post KNIME Tutorial – A Friendly Introduction to Components using the KNIME Analytics Platform appeared first on Analytics Vidhya.

Analytics 377
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Calculating where you should live

FlowingData

Choosing a place to live is always full of trade-offs, but it’d be nice if there was a way to minimize those trade-offs. For NYT Opinion, Gus Wezerek and Yaryna Serkez, made a calculator that lets you weight your priorities to find the city that fits best with how you want to live : Places can score zero to 10 points for each metric. To calculate each place’s match percentage, we add up its scores across metrics that a reader has selected and divide by the total number of possible points.

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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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Informal Mentors Grew into ApplyingML.com!

Eugene Yan

More than two dozen interviews with ML Practitioners sharing their stories and advice

ML 100
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Can You Become a Data Scientist Online?

KDnuggets

Until November 29th, you can join over 1.5 million students around the globe and gain the skills of successful data science professionals with unlimited annual access to the 365 Data Science Program at 72% OFF. Read on to learn more!

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An Introduction to Separable Convolutions

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. We know how useful convolutional neural networks are. CNNs have transformed image analytics. They are the most widely used building blocks for solving problems involving images. Many architectures like ResNet, Google Net have achieved exceptional accuracies in image classification tasks are built with […].

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Communicating effectiveness of boosters

FlowingData

Statisticians David Spiegelhalter and Anthony Masters for The Guardian on reframing risk estimates : An earlier UKHSA study estimated two Pfizer/BioNTech doses gave around 99.7% (97.6% to near-100%) protection against Delta-infected hospitalisation, but after 20 weeks that effectiveness waned to 92.7% (90.3% to 94.6%). This estimated decline for people over 16 may not sound much, but if we look at it in terms of “lack of protection”, their estimated vulnerability relative to being un

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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.