Sat.Nov 19, 2022 - Fri.Nov 25, 2022

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How Much Math Do You Need in Data Science?

KDnuggets

There exist so many great computational tools available for Data Scientists to perform their work. However, mathematical skills are still essential in data science and machine learning because these tools will only be black-boxes for which you will not be able to ask core analytical questions without a theoretical foundation.

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A Comprehensive Guide for Interview Questions on Classical NLP

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Source: Arxiv|Search Engine Journal Introduction As it is common knowledge that natural language processing is one of the most popular and competitive in the current global IT sector. All of the top organizations and budding startups are on the lookout for candidates with […].

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Trending Sources

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How AI revamps financial services and the banking experiences

Dataconomy

We witness more and more artificial intelligence applications in financial services in the post-pandemic era. With the help of artificial intelligence, the banking and finance industries now have new options to satisfy customer expectations for smarter, safer, and more practical ways to access, spend, save, and invest money. The financial.

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A (Software) Bug’s Life

Adrian Bridgwater for Forbes

Software has bugs. Like any major piece of engineering, any building or construction and any architected thing, the likelihood and presence of flaws and snags is almost inevitable.

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Optimizing The Modern Developer Experience with Coder

Many software teams have migrated their testing and production workloads to the cloud, yet development environments often remain tied to outdated local setups, limiting efficiency and growth. This is where Coder comes in. In our 101 Coder webinar, you’ll explore how cloud-based development environments can unlock new levels of productivity. Discover how to transition from local setups to a secure, cloud-powered ecosystem with ease.

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The Inescapable Conclusion: Machine Learning Is Not Like Your Brain

KDnuggets

The final article in this nine-part series summarizes the many reasons why Machine Learning is not like your brain - along with a few similarities.

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4 Artificial Intelligence Approaches to Watch Out For

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Artificial intelligence (AI) is the most dynamic stream in the world. Humans have always been curious about their abilities to predict, understand, act, and make decisions. Now, we can learn everything about it and create intelligent entities with this universal field of […].

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Text Classification using Watson NLP

IBM Data Science in Practice

Leverage the Watson NLP library to build the best classification models by combining the power of classic ML, Deep Learning, and Transformed based models. [link] Text classification is one of the most used NLP tasks for several use cases like email spam filtering, tagging, and classifying content, blogs, metadata, etc. Some of the more specific use cases are Sentiment, Emotion, and Tone classification.

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What is Chebychev’s Theorem and How Does it Apply to Data Science?

KDnuggets

Chebyshev’s Theorem applies to every data set and is heavily used by Statisticians, Data Scientists, and Machine Learning Engineers.

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Data Lineage- Why Are Businesses Eager to Invest?

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Currently, most businesses and big-scale companies are generating and storing a large amount of data in their data storage. Many companies are there which are completely data-driven. Businesses and companies are using data to get some insights about the progress and future […].

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Network Automation 101: What is there to automate, and how is it done?

Dataconomy

Network automation automates the configuration, management, testing, deployment, and operation of physical and virtual devices within a network. The availability of network services increases as routine network operations and functions are automated and repetitive processes are regulated and handled automatically.

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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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Decline of key changes in popular music

FlowingData

Chris Dalla Riva analyzed key changes in songs that made the Billboard Hot 100, between 1958 and 2022. Key changes are near non-existent after 2010. The most interesting part is why : Thus, if you changed the key of “Juicy,” Biggie wouldn’t necessarily have to change how he raps, but if you changed the key of “Over the Rainbow,” Judy Garland would have to sing different pitches.

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10 Amazing Machine Learning Visualizations You Should Know in 2023

KDnuggets

Yellowbrick for creating machine learning plots with less code.

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Creating and Managing DynamoDB Tables using AWS CLI

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Source: [link] Introduction The AWS Command Line Interface (CLI) is a centralized management tool for managing AWS services. Through CLI, users can control services manually or automate them with powerful scripts. With this one tool, it can handle multiple AWS services from the […].

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EU probes TikTok’s data practices with multiple investigations

Dataconomy

TikTok data practices on EU citizens and ads catering to kids are under investigation by the European Union. Allegations include that the social media giant sent European users’ data to China. Following the US, the EU started investigating TikTok’s data practices and its compliance with General Data Protection Regulation (GDPR) requirements.

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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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Why Big Data Is The Future Of Sales And Marketing

Smart Data Collective

Proper marketing and sales prospects play a huge role in improving the success rate of your business. The strategy can either be offline or digital. However, digital marketing has become the major focus of marketers across all industries, mainly due to how customers interact and engage with modern businesses. Seeing an opportunity and knowing how and when to take advantage of it defines the majority of where today’s marketers stand.

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10 Most Common Data Quality Issues and How to Fix Them

KDnuggets

Ensuring data quality guarantees more data-informed decisions. Hence, this article highlights the common data quality issues and ways to overcome them.

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Data Lineage: Case Studies of Data-Driven Businesses

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Data lineage is the process of analyzing the path of the data and how it is involved in different methods with time. Many businesses and companies use it to get an idea of the source, data pathway, and how the data is […]. The post Data Lineage: Case Studies of Data-Driven Businesses appeared first on Analytics Vidhya.

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BIDW: What makes business intelligence and data warehouses inseparable?

Dataconomy

Although they function in the same area, business intelligence and data warehouses are fundamentally different concepts. Data warehouses and business intelligence both include data storage. However, data collection, technique, and analysis are the main focuses of business intelligence. On the other hand, a data warehouse primarily organizes and stores such data.

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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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Data Analytics Solves Manufacturing Marketing Agency Challenges

Smart Data Collective

Data analytics is unquestionably one of the most disruptive technologies impacting the manufacturing sector. Manufacturers are projected to spend nearly $10 billion on analytics by the end of the year. Data analytics can solve many of the biggest challenges that manufacturers face. One of the most significant benefits of leveraging analytics in manufacturing is with marketing optimization and automation.

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Top Posts November 14-20: Git for Data Science Cheatsheet

KDnuggets

Git for Data Science Cheatsheet • 6 Best Free Online Courses to Learn Python and Boost Your Career • How to Select Rows and Columns in Pandas Using [ ],loc, iloc,at and.iat • How LinkedIn Uses Machine Learning To Rank Your Feed • 7 SQL Concepts You Should Know For Data Science.

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Advantages of Using Cloud Data Platform Snowflake

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction The rate of data expansion in this decade is rapid. The requirement to process and store these data has also become problematic. Today, data controls a significant portion of our lives as consumers due to advancements in wireless connectivity, processing power, and […].

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Your guide to assessing cybersecurity risks before they harm valuable assets

Dataconomy

Cybersecurity risk assessment is essential for any organization at any stage of its digital transformation journey. Almost all businesses have some IT infrastructure and internet connectivity, which makes them all vulnerable against cyber threats to some extent.

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The Cloud Development Environment Adoption Report

Cloud Development Environments (CDEs) are changing how software teams work by moving development to the cloud. Our Cloud Development Environment Adoption Report gathers insights from 223 developers and business leaders, uncovering key trends in CDE adoption. With 66% of large organizations already using CDEs, these platforms are quickly becoming essential to modern development practices.

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Is Artificial Intelligence Setting A New Standard For Web Design?

Smart Data Collective

Artificial intelligence is playing an important role in modern creative professions. There are a lot of reasons a growing number of companies are turning to AI technology. One poll showed that 61% of companies found that AI and machine learning were their best data investments. One of the industries that is evolving by adopting new AI tools in web design.

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How to Use Graph Theory to Scout Soccer

KDnuggets

Take Soccer Analytics to the Next Level with Graph Theory: Here’s What to Know and How to Do It.

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Build AI Web App using Azure Cognitive Services

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Web apps are the apps through which you can showcase your solution or approach to the public at a mass level. Creating the model is not enough until it’s in use by people. When it comes to delivering the solution then, everyone […]. The post Build AI Web App using Azure Cognitive Services appeared first on Analytics Vidhya.

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The role of intelligent data in driving supply chain efficacy

Dataconomy

As supply chains in the US and around the world remain tumultuous, facing pandemic closures and labor shortages, supply chain professionals are turning to data to stay ahead. An intelligent supply chain, supported by live data, enables real-time collaboration, faster execution speeds, and improved accountability. Inventory shortages have become an.

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How to Drive Cost Savings, Efficiency Gains, and Sustainability Wins with MES

Speaker: Nikhil Joshi, Founder & President of Snic Solutions

Is your manufacturing operation reaching its efficiency potential? A Manufacturing Execution System (MES) could be the game-changer, helping you reduce waste, cut costs, and lower your carbon footprint. Join Nikhil Joshi, Founder & President of Snic Solutions, in this value-packed webinar as he breaks down how MES can drive operational excellence and sustainability.

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The Obscure Art of Data Design

Cassie Kozyrkov

Battling an embarrassing new alchemy for the digital era Continue reading on Towards Data Science »

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Linux for Data Science Cheatsheet

KDnuggets

KDnuggets is back with another exclusive cheatsheet, this time sharing a Linux quick reference for data science.

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5 Most Challenging Interview Questions on TensorFlow

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Source: totaljobs.com Introduction TensorFlow is one of the most promising deep learning frameworks for developing cutting-edge deep learning solutions. Given the popularity and extensive usage of TensorFlow in the industry to automate processes and create new tools, it is imperative to have a […].

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Movio AI narrates your stories with lifelike AI avatars capable of convincing lip sync, gestures and expressions

Dataconomy

Movio AI spokesperson video generator is ready to tell your story convincingly. The AI video generator render processes are fairly quick, and videos are ready to publish in just a few minutes! How is it possible? Movio AI combines generative AI with other machine learning frameworks like generative adversarial networks.

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Improving the Accuracy of Generative AI Systems: A Structured Approach

Speaker: Anindo Banerjea, CTO at Civio & Tony Karrer, CTO at Aggregage

When developing a Gen AI application, one of the most significant challenges is improving accuracy. This can be especially difficult when working with a large data corpus, and as the complexity of the task increases. The number of use cases/corner cases that the system is expected to handle essentially explodes. 💥 Anindo Banerjea is here to showcase his significant experience building AI/ML SaaS applications as he walks us through the current problems his company, Civio, is solving.