Sat.Jul 30, 2022 - Fri.Aug 05, 2022

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How to Deal with Categorical Data for Machine Learning

KDnuggets

Check out this guide to implementing different types of encoding for categorical data, including a cheat sheet on when to use what type.

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Introduction to Requests Library in Python

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Requests in Python is a module that can be used to send all kinds of HTTP requests. It is straightforward to use and is a human-friendly HTTP Library. Using the requests library; we do not need to manually add the query string […]. The post Introduction to Requests Library in Python appeared first on Analytics Vidhya.

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Scaling False Peaks

O'Reilly on Data

Humans are notoriously poor at judging distances. There’s a tendency to underestimate, whether it’s the distance along a straight road with a clear run to the horizon or the distance across a valley. When ascending toward a summit, estimation is further confounded by false summits. What you thought was your goal and end point turns out to be a lower peak or simply a contour that, from lower down, looked like a peak.

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Expanding the Analytics Continuum: From Analysis to Action

David Menninger's Analyst Perspectives

I often use the term “analytics” to refer to a broad set of capabilities, deliberately broader than business intelligence. In this Perspective, I’d like to share what decision-makers should consider as they evaluate the range of analytics requirements for their organization.

Analytics 162
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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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Most In-demand Artificial Intelligence Skills To Learn In 2022

KDnuggets

Artificial Intelligence (AI) is the process of programming a computer that can reason and learn like a human being and make decisions for itself.

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Step-by-Step Exploratory Data Analysis (EDA) using Python

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction to EDA The main objective of this article is to cover the steps involved in Data pre-processing, Feature Engineering, and different stages of Exploratory Data Analysis, which is an essential step in any research analysis. Data pre-processing, Feature Engineering, and EDA are fundamental early […].

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Predictive Analytics Improves Trading Decisions as Euro Rebounds

Smart Data Collective

Modern investors have a difficult time retaining a competitive edge without having the latest technology at their fingertips. Predictive analytics technology has become essential for traders looking to find the best investing opportunities. Predictive analytics tools can be particularly valuable during periods of economic uncertainty. Traders can have even more difficulty identifying the best investing opportunities as market volatility intensifies.

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Getting Started with SQL Cheatsheet

KDnuggets

Want to get started with SQL? Check out the latest cheatsheet from KDnuggets to get up to speed on the basics of one of the most popular, useful, and in-demand languages in the world of data science.

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Multi-variate Time Series Forecasting using Kats Model

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Kats model-which is also developed by Facebook Research Team-supports the functionality of multi-variate time-series forecasting in addition to univariate time-series forecasting. Often we need to forecast a time series where we have input variables in addition to ‘time’; this is where the […].

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The Right Stuff: The Role of MLOps in AI Success

CIO Business Intelligence

Great teams incorporate a variety of skill sets. For example, a football team consisting of 11 quarterbacks would get crushed in a game against talented linemen, running backs and receivers. It’s no different when building a team for an enterprise AI project; you can’t just throw a bunch of data scientists into a room and expect them to come up with a revenue-generating or efficiency-improving project without support from other members of the enterprise.

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8 Steps to Transformation at Speed & Scale – Your Guide to Deploying StratOps

📌Is your Data & AI transformation struggling to really impact the business? Discover the game-changing StratOps approach that: Bridges the Gap : Connect your Data & AI strategy to your operating model, to ensure alignment at every level. Prioritizes Outcomes : Focuses on concrete business outcomes from day one, rather than capabilities in isolation.

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SQL Server and the Cast Function for Data-Driven Companies

Smart Data Collective

A growing number of businesses are relying on big data technology to improve productivity and address some of their most pressing challenges. Global companies are projected to spend over $297 billion on big data by 2030. Data technology has proven to be remarkably helpful for many businesses. However, companies also encounter a number of challenges as they try to leverage the benefits of big data.

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A community developing a Hugging Face for customer data modeling

KDnuggets

A year ago, Objectiv started a community of 50 companies to develop a Hugging Face like open-source project for customer data modeling. They key objective: enable building data models on one team/company’s dataset, and then run them seamlessly on another.

Modeling 132
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12 FAQs on AWS Asked in Interviews

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction The way big business tycoons run has changed a lot since the past. The concept of “Cloud Computing” has played a major role in this. This implementation of cloud computing technology has led to the need for Cloud Computing Experts. The software team […].

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5 forces shaping the future IT workforce

CIO Business Intelligence

Concerns about a looming recession have not derailed the booming IT job market. In the first half of this year, 115,000 new IT jobs were added, according to consulting firm Janco Associates. Even with inflation, high energy costs, and the invasion of Ukraine, IT hiring continued at a record-setting pace, but keeping tech talent still poses challenges.

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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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Data-Driven Employee Reviews Are Less Biased and Unfair

Smart Data Collective

Data analytics technology has changed many aspects of the modern workplace. A growing number of companies are using data to make more informed hiring decisions , track payroll issues and resolve internal problems. One of the most important benefits of data analytics is that it can help companies monitor employee performance and provide more accurate feedback.

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Free MLOps Crash Course for Beginners

KDnuggets

Interest in, and demand for, MLOps is growing exponentially. What, exactly, is it? Why is it important? Where should you turn next to learn more? Check out this crash course to find the answers to these questions and more.

IT 123
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Bridging the Gap: Drug Discovery and AI

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction This problem that we will discuss in this blog comes from the cutting-edge intersection of AI with the drug discovery process, where DataRobot and my team play a very significant role. This blog is focused on an engagement my team, and I […]. The post Bridging the Gap: Drug Discovery and AI appeared first on Analytics Vidhya.

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NLP helps Eli Lilly work at a global scale

CIO Business Intelligence

With more than 30,000 employees spread across more than 60 affiliate locations and 14 manufacturing sites around the world, pharmaceutical company Eli Lilly operates at a truly global scale. Operating at that scale comes with issues, not the least of which is sharing accurate and timely information internally and externally. “From internal training materials to formal, technical communications to regulatory agencies, Lilly is translating information often,” says Timothy F.

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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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How AI Software is Changing the Future of the Automotive Industry

Smart Data Collective

Artificial intelligence technology is changing the future of many industries. Global companies spent over $328 billion on AI last year. This figure is expected to grow as more companies recognize the potential and decide to increase the resources they dedicate to machine learning and predictive analytics tools. The automotive industry is among those investing in AI the most.

Software 129
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Machine Learning Is Not Like Your Brain Part 6: The Importance of Precise Synapse Weights and the Ability to Set Them Quickly

KDnuggets

In Part Six, I’ll show how limitations in synapses are even more of a problem. Precise synapse weights and the ability to set them quickly to a specific value are crucial to ML and biological neurons offer neither.

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The DataHour: Improving Search Results with Semantic Search

Analytics Vidhya

Dear Readers, Have you ever wondered about the uncanny ability of google to complete your sentences even before you complete them? Or the fact that Google or any other search engine can comprehend a sentence’s meaning and provide precise responses to the featured excerpts. It appears that Google uses mystical means to “think” and exercise […].

Analytics 380
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94% of enterprises are overspending in the cloud: report

CIO Business Intelligence

A vast majority of enterprises globally are overspending in the cloud, according to a new HashiCorp-Forrester report. In a survey that saw participation of over 1,000 IT decision makers across North America, Europe, Middle East and Asia-Pacific, 94% of respondents said their organizations had notable, avoidable cloud spend due to a combination of factors including underused, overprovisioned resources, and lack of skills to utilize cloud infrastructure.

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The Ultimate Guide To Data-Driven Construction: Optimize Projects, Reduce Risks, & Boost Innovation

Speaker: Donna Laquidara-Carr, PhD, LEED AP, Industry Insights Research Director at Dodge Construction Network

In today’s construction market, owners, construction managers, and contractors must navigate increasing challenges, from cost management to project delays. Fortunately, digital tools now offer valuable insights to help mitigate these risks. However, the sheer volume of tools and the complexity of leveraging their data effectively can be daunting. That’s where data-driven construction comes in.

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Wi-Fi Connectivity Issues Impede Data-Driven Healthcare Models

Smart Data Collective

Analytics technology has transformed the healthcare industry in recent years. Healthcare organizations are projected to spend over $80 billion on analytics services by 2028. There are many benefits of leveraging analytics in healthcare. Hospitals and individual healthcare providers are using analytics tools to predict the likelihood a patient will develop a disease, minimize medical error rates, reduce costs of delivering treatment and provide a better overall patient experience.

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Preparing for a Data Analyst Interview

KDnuggets

The interview process for the job can sometimes be a bit daunting. However, with the right knowledge and preparation, you can make sure you ace the interview and land your dream job. Read this summary of DataCamp’s full article on how to prepare for a data analyst interview, presenting some of the key points. .

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Introduction to Intelligent Search Algorithms

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction to Intelligent Search Algorithms Search problems are widespread in real-world applications. Search algorithms are beneficial in simplifying or solving the problems such as searching a database or the internet. One of the most popular search problems is to find the shortest path […].

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Global RPA software sales forecast to jump this year

CIO Business Intelligence

Driven by the ongoing need for companies to automate repetitive tasks, global RPA (robotic process automation) software revenue is expected to reach $2.9 billion in 2022, up by 19.5% from last year, according to a market research report by Gartner. North America will account for the largest revenue share at 48.5%, followed by Western Europe and Japan at 19% and 10% respectively, Gartner said.

Software 122
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Launching LLM-Based Products: From Concept to Cash in 90 Days

Speaker: Christophe Louvion, Chief Product & Technology Officer of NRC Health and Tony Karrer, CTO at Aggregage

Christophe Louvion, Chief Product & Technology Officer of NRC Health, is here to take us through how he guided his company's recent experience of getting from concept to launch and sales of products within 90 days. In this exclusive webinar, Christophe will cover key aspects of his journey, including: LLM Development & Quick Wins 🤖 Understand how LLMs differ from traditional software, identifying opportunities for rapid development and deployment.

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Steps Laptop Owners Must Take to Mitigate Risks of Data Loss

Smart Data Collective

Data loss is a growing problem, as companies become more dependent on data than ever. The cost of data loss can be massive for many companies. A data center outage can cost $7,900 in losses every minute. However, the cost of losing data on a regular computer can be significant as well. Many people store valuable company data on their laptops. Some people also store cryptocurrency wallets on their personal computers.

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AI for Time Travel? Well, Almost

Dataiku

AI predictions compress time: Reduce credit card refunds from 60 to 30 days or time to detect chip manufacturing problems from 36 hours to zero. Increasingly, companies are going beyond zero and using AI to detect things before they happen: identifying the purchase of a large screen TV with a stolen credit card hours before it happens, replacing an airplane valve days before it fails, and flagging semiconductor manufacturing defects an hour before they’re produced.

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Training CNN from Scratch Using the Custom Dataset

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction In certain circumstances, using pre-built frameworks from machine learning and deep learning libraries may be beneficial. However, you should attempt to put things into practice on your own to have good command and comprehension. This article demonstrates how to create a CNN […].

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Steps CIOs should take to protect customer data in Nigeria’s open banking systems

CIO Business Intelligence

Due to Nigeria’s fintech boom borne out of its open banking framework, the Central Bank of Nigeria (CBN) has published a much-awaited regulation draft to govern open banking procedures. And at its core is the need to secure customer data through a robust set of requirements. The regulations streamline how entities who handle customer banking information will secure their systems and share details within protected application program interfaces.

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Data Modeling for Direct Mail: Boosting Multi-Channel Reach and Response

Speaker: Jesse Simms, VP at Giant Partners

This new, thought-provoking webinar will explore how even incremental efforts and investments in your data can have a tremendous impact on your direct mail and multi-channel marketing campaign results! Industry expert Jesse Simms, VP at Giant Partners, will share real-life case studies and best practices from client direct mail and digital campaigns where data modeling strategies pinpointed audience members, increasing their propensity to respond – and buy.