Sat.Aug 31, 2019 - Fri.Sep 06, 2019

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The Data-Centric Revolution: Toss Out Metadata That Does Not Bring Joy

TDAN

As I write this, I can almost hear you wail “No, no, we don’t have too much metadata, we don’t have nearly enough! We have several projects in flight to expand our use of metadata.” Sorry, I’m going to have to disagree with you there. You are on a fool’s errand that will just provide […].

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Make Sure You Know The Difference Between Strategic, Analytical, Operational And Tactical Dashboards

datapine

The secret is out, and has been for a while: In order to remain competitive, businesses of all sizes, from startup to enterprise, need business intelligence (BI). Business intelligence has evolved into smart solutions that provide effective data management – from extracting, monitoring, analyzing, and deriving actionable insights needed to stay competitive on the market, to powerful visualizations created with a dashboard builder which enables business users to interact with data and drill into

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The Consequence of Valuing Data

Andrew White

For years theorists, economists, and even tech-evangelists, have all been arguing over the value of data. Notwithstanding the hype, even the Economist in 2017 suggested in a leader article that data was the new oil. Gartner has been writing about ‘data as an asset’ for years. We even ratified calculations to help determine and quantify the value of data assets.

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Here are 7 Data Science Projects on GitHub to Showcase your Machine Learning Skills!

Analytics Vidhya

Overview Working on Data Science projects is a great way to stand out from the competition Check out these 7 data science projects on. The post Here are 7 Data Science Projects on GitHub to Showcase your Machine Learning Skills! appeared first on Analytics Vidhya.

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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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Using Automation to Cut Through the Clutter By Yellowfin

Corinium

Mobile BI should extend your ability to discover, collaborate, and act on insights and create an inclusive and effective data culture. The best mobile apps have simple-to-use tools designed specifically with mobile in mind that mean you always know when, what and, importantly, why something changed in your data. Download your copy of 'Mobile-Focused BI: Using Automation to Cut Through the Clutter' to find out more on making analytic insights instantly actionable everywhere.

Analytics 150
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TensorFlow vs PyTorch vs Keras for NLP

KDnuggets

These three deep learning frameworks are your go-to tools for NLP, so which is the best? Check out this comparative analysis based on the needs of NLP, and find out where things are headed in the future.

More Trending

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Everything you Should Know about p-value from Scratch for Data Science

Analytics Vidhya

Overview What is p-value? Where is it used in data science? And how can we calculate it? We answer all these questions and more. The post Everything you Should Know about p-value from Scratch for Data Science appeared first on Analytics Vidhya.

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Interview with: Aditya Kumbakonam, Co-founder & Head of Client Services, Delivery at TheMathCompany

Corinium

Tell us about your experience in working with the data analytics community at TheMathCompany? Why do you like working in this space?

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Advice on building a machine learning career and reading research papers by Prof. Andrew Ng

KDnuggets

This blog summarizes the career advice/reading research papers lecture in the CS230 Deep learning course by Stanford University on YouTube, and includes advice from Andrew Ng on how to read research papers.

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Top 10 BI data visualization tools

CIO Business Intelligence

There is golden knowledge in the sea of data that businesses are swimming in. Being able to fish out the business intelligence you need — when you need it — is the key to steering your ship.

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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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Step-by-Step Deep Learning Tutorial to Build your own Video Classification Model

Analytics Vidhya

Overview Learn how you can use computer vision and deep learning techniques to work with video data We will build our own video classification. The post Step-by-Step Deep Learning Tutorial to Build your own Video Classification Model appeared first on Analytics Vidhya.

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Kaggle Learn Micro-courses

Data Science 101

The competition site Kaggle has recently released some micro-courses aimed at helping people to quickly learn the skills of data science. It is called Kaggle Learn, Faster Data Science Education. It includes courses on: Python Deep Learning SQL and more. Check them out to quickly get up to speed. Happy Learning.

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An Overview of Topics Extraction in Python with Latent Dirichlet Allocation

KDnuggets

A recurring subject in NLP is to understand large corpus of texts through topics extraction. Whether you analyze users’ online reviews, products’ descriptions, or text entered in search bars, understanding key topics will always come in handy.

Modeling 112
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IDC report names IBM the #1 market leader in AI

IBM Big Data Hub

Among organizations investing in AI hardware, software or services, more will buy IBM and rely on Watson than any other vendor. This according to a new IDC report which names IBM as 2018’s market leader in AI. So just what sets apart IBM as leader of the AI provider pack?

Marketing 101
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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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Feature Engineering for Images: A Valuable Introduction to the HOG Feature Descriptor

Analytics Vidhya

Overview Learn the inner workings and math behind the HOG feature descriptor The HOG feature descriptor is used in computer vision popularly for object. The post Feature Engineering for Images: A Valuable Introduction to the HOG Feature Descriptor appeared first on Analytics Vidhya.

Analytics 261
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Semantic Search or Knowing Your Customers So Well, You Can Finish Their Sentences For Them

Ontotext

My great grandparents were married for more than sixty years. They had a telepathy that comes from living together that long. They could finish each other’s sentences or anticipate when one wanted a coffee or lunch. An exchange could go like this. ‘Remember those figs?’ Grandma said. ‘You’re talking about that holiday to France in ’76 and it wasn’t figs, it was apples.’.

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Python Libraries for Interpretable Machine Learning

KDnuggets

In the following post, I am going to give a brief guide to four of the most established packages for interpreting and explaining machine learning models.

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Data Scientists, The 5 Graph Algorithms that you should know

MLWhiz

We as data scientists have gotten quite comfortable with Pandas or SQL or any other relational database. We are used to seeing our users in rows with their attributes as columns. But does the real world really behave like that? In a connected world, users cannot be considered as independent entities. They have got certain relationships between each other and we would sometimes like to include such relationships while building our machine learning models.

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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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The Role of Big Data In The Promotion of eLearning Courses

Smart Data Collective

We have talked extensively about the role of big data in marketing in previous articles. However, most of our articles relate to the use of big data with traditional marketing channels, including older digital marketing outlets. There are a number of new channels that use big data as well. Push notifications are among them. Hacker Moon wrote an article on the role of big data with push notifications.

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Why Your Company Needs Python for Business Analytics

DataCamp

Learn why Python is so important, and how it’s useful across industries and all fields of business analytics.

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An Easy Introduction to Machine Learning Recommender Systems

KDnuggets

Recommender systems are an important class of machine learning algorithms that offer "relevant" suggestions to users. Categorized as either collaborative filtering or a content-based system, check out how these approaches work along with implementations to follow from example code.

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Delivering boring AI with Decision Management

Decision Management Solutions

A great article appeared in Information Age recently based on an interview with Tom Davenport If you want to see the benefits of AI, forget moonshots and think boring. In it, Tom argues that “if enterprises ever want to see the benefits of AI, they must embrace the mundane”. This is particularly true for companies that aren’t tech startups. As Tom says, “moonshots are possible if you’re a tech giant and you have billions of dollars to spend on experimenting” but what if you can’t “pivot”?

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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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How to Build a Performant Data Warehouse in Redshift

Sisense

Blog. Having seven years of experience with managing Redshift , a fleet of 335 clusters, combining for 2000+ nodes, we (your co-authors Neha, Senior Customer Solutions Engineer, and Chris, Analytics Manager, here at Periscope Data by Sisense) have had the benefit of hours of monitoring their performance and building a deep understanding of how best to manage a Redshift cluster.

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Big Data’s Role In Childbirth And Maternal Death In The US

Smart Data Collective

Maternal mortality rates in the United States jumped over 25% between 2000 and 2013. The CDC uses data to better understand why the United States has the highest maternal death rates in the developed world. Big data allows researchers to dig deeper into the issue to better understand what’s occurring that’s leading to increased deaths for mothers. Understaffed hospitals and medical errors are causing most of the deaths.

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Automated Machine Learning: Just How Much?

KDnuggets

This is an interview between Rosaria Silipo and data scientists Paolo Tamagnini, Simon Schmid and Christian Dietz, asking a few questions on the topic of automated machine learning from their point of view, and some interesting examples of its practical use.

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HyperOpt: Bayesian Hyperparameter Optimization

Domino Data Lab

This article covers how to perform hyperparameter optimization using a sequential model-based optimization (SMBO) technique implemented in the HyperOpt Python package. There is a complementary Domino project available. Introduction. Feature engineering and hyperparameter optimization are two important model building steps. Over the years, I have debated with many colleagues as to which step has more impact on the accuracy of a model.

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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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Taking Smarter Risks to Monetize Your Data

Sisense

Blog. For modern organizations, data is the ultimate building block. High profile companies are using data to build profitable new products, new lines of business, even entirely new industries. It’s the starting point and the finish line for every new business creation. In an age where every company is making moves to be more data-driven, those that figure out how to efficiently monetize their data insights will be the biggest winners.

Risk 75
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Consolidating Patron’s Data – To Increase Casinos’ ROI

BizAcuity

Admit it or not, casinos are booming to become a much bigger playground for businesses. With most operating within a hotel-like framework, there are more ways to engage their customers than ever before. From an operational standpoint, this means that casino-owners need to deploy different systems in different places across the floor of the casino to ensure seamless functioning.

ROI 75
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Automate your Python Scripts with Task Scheduler: Windows Task Scheduler to Scrape Alternative Data

KDnuggets

In this tutorial, you will learn how to run task scheduler to web scrape data from Lazada (eCommerce) website and dump it into SQLite RDBMS Database.

IT 103
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How Data Strategy and Machine Learning Intersect

TDAN

Are you worried about the security of your valuable data? Well, with the massive growth of business data in terms of complexity, volume and size, it is basic for worldwide associations to build up a strong data technique to address the main business needs. If you are working in an IT vertical then it is […].

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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.