Thu.Dec 15, 2022

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Meta-Reinforcement Learning in Data Science

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Generally, machine learning can be classified into four types: supervised machine learning, unsupervised machine learning, semi-supervised machine learning, and reinforcement learning. Supervised machine learning is a type of machine learning that is the easiest and less complex type or branch of data science. […].

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Recognize and Plan for the AI and Machine Learning Skills Gap

David Menninger's Analyst Perspectives

Recently, I suggested you need to “ mind the gap” between data and analytics. This perspective addresses another gap — the gap in skills between business intelligence (BI) and artificial intelligence/machine learning (AI/ML).

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Introduction to HyperLedger Fabric in Blockchain Network

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction HyperLedger Fabric is a permissioned blockchain infrastructure initially developed by IBM and Digital Asset. It is used for providing a modular architecture with a delineation of roles between the nodes in the infrastructure. It is also used in the execution of various Smart […].

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Maryfran Johnson, Host of the CIO Leadership Live video podcast, CEO Maryfran Johnson Media

CIO Business Intelligence

It’s a wrap. Lee interviews Maryfran Johnson about 2022 trending themes in technology as discussed with CIOs on CIO Leadership Live. Watch this episode: Listen to this episode: CIO Leadership Live.

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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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10 Common AWS S3 Mistakes

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Are you using Amazon Web Services (AWS) Simple Storage Service (S3) to store your data and media files? If so, you’re not alone – AWS S3 is a popular choice for its scalability and reliability. However, it’s not uncommon to make common AWS […]. The post 10 Common AWS S3 Mistakes appeared first on Analytics Vidhya.

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5 Python Projects for Data Science Portfolio

KDnuggets

Get more experience by working on web scraping, data analytics, time-series forecasting, machine learning, and deep learning projects.

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Tuning Adam Optimizer Parameters in PyTorch

KDnuggets

Choosing the right optimizer to minimize the loss between the predictions and the ground truth is one of the crucial elements of designing neural networks.

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Safety First: Using vehicle data to make us all better drivers

Teradata

Vehicle data is invaluable in improving the safety & safe operation of vehicles for their occupants & other drivers. The next gen of vehicles will use real-time analysis to make driving even safer.

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Be prepared to manage the threat with an MS in Cybersecurity from Bay Path University

KDnuggets

Bay Path’s Master’s in Cybersecurity prepares students to step into the workforce and assume immediate responsibility for the management and oversight of such systems.

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How IEC 62443 and Other Regulatory Requirements Help Enable IoT Security

Smart Data Collective

As the US Government Accountability Office warns, “ internet-connected technologies can improve services, but face risks of cyberattacks.” The use of IoT devices and operational technology (OT) generates new attack surfaces that can expose an organization’s critical infrastructure to hackers and other threat actors. Building access gadgets, badge readers, fuel usage and route monitors (for vehicle fleets), and apps that connect to the enterprise IT infrastructure create, among others, can

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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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SAP user groups see pick-up in migration to S/4HANA

CIO Business Intelligence

Enterprise adoption of SAP S/4HANA continues to climb despite the obstacles in its way, according to new research by user groups in the US and Europe. Adopters are being drawn by advanced capabilities in the new software, and driven by concerns about maintenance of older systems. In the UK and Ireland, 89% of SAP customers are either using or planning to use S/4HANA, up from 74% in 2021, according to a survey conducted for the UK & Ireland SAP User Group (UKISUG).

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Do you need coding skills to build a chatbot?

IBM Big Data Hub

Virtual assistants are valuable, transformative business tools that offer a compelling ROI while improving the customer experience. By 2030, conversational AI chatbots and virtual assistants will handle 30% of interactions that would have otherwise been handled by a human agent—up from 2% in 2022. [i] So why haven’t more companies adopted this solution?

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YOLOv5 PyTorch Tutorial

KDnuggets

Learn and train object detection model using YOLOv5.

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Creating an Agile BI infrastructure with Data Virtualization

Data Virtualization

Reading Time: 3 minutes One of the biggest challenges for organizations is to integrate data from various sources. Despite modern advancements such as big data technologies and cloud, data often ends up in organized silos, but this means that cloud data is separated from. The post Creating an Agile BI infrastructure with Data Virtualization appeared first on Data Virtualization blog - Data Integration and Modern Data Management Articles, Analysis and Information.

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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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Financial Services and Insurance: Driving Tomorrow’s Data Science Trends

Domino Data Lab

Last week Domino celebrated data science innovators driving breakthroughs in health and life sciences. This week we announce a new slate of innovators in the Financial Services and Insurance edition of the Data Science Innovator’s Playbook, available now as a free download. As before, each of its top data science innovation leaders in the financial services and insurance industries share insights on their work, careers, and the data science profession.

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Building a Data Science Escape Room With Dataiku

Dataiku

Escape rooms have become a go-to activity for team building events and other social gatherings — but did you know that you can build your own with Dataiku? A group of our finest data analysts and software engineers did just that, ultimately creating both an online and an in-person version of the game that set groups of Dataiku users of varying skill levels in a race against the clock to crack the code.

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10 Years Later: Who’s the GOAT of Data Catalogs?

Alation

Founded on 12/12/12, Alation celebrated its 10th year in business this week. Among all the internal celebrations, I wanted to take this moment to reflect on our journey so far and ask a thought-provoking question: who is the GOAT of data catalogs ? What Is a GOAT? If you follow professional sports, you’re likely familiar with GOATs. For those that are unaware, this acronym stands for the “Greatest Of All Time.”.

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KDnuggets Top Posts for November 2022: What is Chebychev’s Theorem and How Does it Apply to Data Science?

KDnuggets

What is Chebychev's Theorem and How Does it Apply to Data Science? • Git for Data Science Cheatsheet • 7 SQL Concepts Needed for Data Science • The Complete Data Engineering Study Roadmap •. Linux for Data Science Cheatsheet • Confusion Matrix, Precision, and Recall Explained • 9 Free Resources to Master Python • Matrix Multiplication for Data Science (or Machine Learning).

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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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Implement a Multi-Cloud Open Lakehouse with Apache Iceberg in Cloudera Data Platform

Cloudera

Since we announced the general availability of Apache Iceberg in Cloudera Data Platform (CDP), Cloudera customers, such as Teranet , have built open lakehouses to future-proof their data platforms for all their analytical workloads. Cloudera partners are also benefiting from Apache Iceberg in CDP. For example, Modak Nabu is helping their enterprise customers accelerate data ingestion, curation, and consumption at petabyte scale.

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Sustainable Petrochemical Company Expands Risk-Based Inspection Philosophy

CIO Business Intelligence

PET is a major industrial polymer used to manufacture the polyester fibers used in clothing, plastic bottles, and much more. As such, it is the most widely recycled plastic in the world. As a global chemical company and producer of PET, Indorama Ventures Limited (IVL) has made sustainability a priority for over a decade, from energy and greenhouse gas reductions to increased renewable energy and recycling.

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Better Forecasting with AI-Powered Time Series Modeling

DataRobot Blog

AI-powered Time Series Forecasting may be the most powerful aspect of machine learning available today. Working from datasets you already have, a Time Series Forecasting model can help you better understand seasonality and cyclical behavior and make future-facing decisions, such as reducing inventory or staff planning. By simplifying Time Series Forecasting models and accelerating the AI lifecycle, DataRobot can centralize collaboration across the business—especially data science and IT teams—an

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How the digital HQ can deliver efficiency and productivity—even in challenging times

CIO Business Intelligence

Chris Mills, Head of Customer Success, EMEA at Slack The roles of the CTO and CIO have grown enormously in recent years, proving fundamental in facilitating the rapid shift from traditional working to hybrid working during the pandemic. But this was no short term shift—the value of the CTO and CIO continues to rise. The next challenge on the horizon?

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The Path to Product Excellence: Avoiding Common Pitfalls and Enhancing Communication

Speaker: David Bard, Principal at VP Product Coaching

In the fast-paced world of digital innovation, success is often accompanied by a multitude of challenges - like the pitfalls lurking at every turn, threatening to derail the most promising projects. But fret not, this webinar is your key to effective product development! Join us for an enlightening session to empower you to lead your team to greater heights.

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8 Ways AI Contributes to Ecommerce Business Scalability

Smart Data Collective

Artificial intelligence has offered a plethora of benefits for businesses in every sector. The ecommerce industry is among those most benefiting from advances in AI. Therefore, it is no surprise that the market for AI-enabled ecommerce services is projected to be worth nearly $17 billion by 2030. Ecommerce giants like Amazon are finding creative ways to leverage AI.

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The Benefits of a Knowledge Graph-based Metadata Hub

Ontotext

Today’s enterprises are increasingly daunted by the realization that more data doesn’t automatically equal deeper knowledge and better business decisions. The mere existence of the 175 zettabytes of data the International Data Corporation estimates the world will possess by 2025 doesn’t matter if organizations can’t leverage it effectively. Obviously, not all of that data is accessible to businesses, but what they can access is still overwhelming.

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Lenovo Research Shows The Next Stage Of Transformation Is Human Centricity

CIO Business Intelligence

The demand for ongoing transformation and innovation is going to continue to drive IT budgets into 2023. As a solution to the challenges of inflation, recession, geopolitical instability, and the broader economy, IT is seen as the way forward. Research shows that more than half – 52 per cent – of organisations are expecting to increase spending in IT.