Decision Management Solutions
AUGUST 8, 2019
Trust is a big deal when it comes to machine learning. “Black box” algorithms, concerns about bias and a sense that data scientists may know everything about the data but nothing about the business all undermine trust in machine learning models. Indeed, building machine learning models that can be, will be, trusted is regarded as a critical issue for many data science teams.
TDAN
AUGUST 6, 2019
All businesses, no matter the industry or focus, are completely inundated by data. After all, we live in a very competitive world and data can help everyone improve their business performance. One could also argue that with this abundance of data, there is also a rise of new technologies, frameworks, and methodologies which can help […].
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erwin
AUGUST 7, 2019
A data catalog benefits organizations in a myriad of ways. With the right data catalog tool, organizations can automate enterprise metadata management – including data cataloging, data mapping, data quality and code generation for faster time to value and greater accuracy for data movement and/or deployment projects. Data cataloging helps curate internal and external datasets for a range of content authors.
Teradata
AUGUST 4, 2019
Self-service analytics are increasingly being implemented by organizations that want to promote a data-driven culture. But how sustainable is it? Read more.
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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have migrated their testing and production workloads to the cloud, yet development environments often remain tied to outdated local setups, limiting efficiency and growth.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.
Analytics Vidhya
AUGUST 5, 2019
Overview Evaluating a model is a core part of building an effective machine learning model There are several evaluation metrics, like confusion matrix, cross-validation, The post 11 Important Model Evaluation Metrics for Machine Learning Everyone should know appeared first on Analytics Vidhya.
Domino Data Lab
AUGUST 5, 2019
This Domino Data Science Field Note covers Chris Wiggins ‘s recent data ethics seminar at Berkeley. The article focuses on 1) proposed frameworks for defining and designing for ethics and for understanding the forces that encourage industry to operationalize ethics, as well as 2) proposed ethical principles for data scientists to consider when developing data-empowered products.
Data Leaders Brief brings together the best content for data, strategy, and BI professionals from the widest variety of industry thought leaders.
datapine
AUGUST 7, 2019
In the Age of Information, digital technologies have evolved to such an extent that a wealth of tools, applications, and platforms exists to enhance the way businesses operate in a number of areas. Software as a service (SaaS) has blossomed in the last five years, and the public SaaS market is expected to grow to $76 billion by the year 2020, according to FinancesOnline.
Analytics Vidhya
AUGUST 6, 2019
Overview Real-time object detection is taking the computer vision industry by storm Here’s a step-by-step introduction to SlimYOLOv3, the latest real-time object detection framework. The post A Friendly Introduction to Real-Time Object Detection using the Powerful SlimYOLOv3 Framework appeared first on Analytics Vidhya.
Corinium
AUGUST 6, 2019
The Fourth Industrial Revolution is, ostensibly, upon us. The term was coined in 2016 by Klaus Schwab, the founder and executive chairman of the World Economic Form.
KDnuggets
AUGUST 8, 2019
Graph Machine Learning uses the network structure of the underlying data to improve predictive outcomes. Learn how to use this modern machine learning method to solve challenges with connected data.
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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?
Smart Data Collective
AUGUST 7, 2019
Big data has the power to transform any small business. However, many small businesses don’t know how to utilize it. One study found that 77% of small businesses don’t even have a big data strategy. If your company lacks a big data strategy, then you need to start developing one today. The best thing that you can do is find some data analytics tools to solve your most pressing challenges.
Analytics Vidhya
AUGUST 7, 2019
Overview Language models are a crucial component in the Natural Language Processing (NLP) journey These language models power all the popular NLP applications we. The post A Comprehensive Guide to Build your own Language Model in Python! appeared first on Analytics Vidhya.
Corinium
AUGUST 4, 2019
Joining us at the Chief Data & Analytics Officer Melbourne (9-11 September), we are pleased to welcome Pieter Vorster, Executive General Manager, Customer Solutions & Insights at Bankwest. He shares his insight on the knowledge gap growing between decision-makers and data specialists.
KDnuggets
AUGUST 7, 2019
Learn about Artificial Neural Networks, Deep Learning, Recurrent Neural Networks and LSTMs like never before and use NLP to build a Chatbot!
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📌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.
Dataiku
AUGUST 9, 2019
Between growing data and analytics teams, more collaborative projects, and GDPR , security and governance are becoming bigger issues. As organizations' analytical maturity improves, it's increasingly critical that business and technical users alike understand data best practices.
Analytics Vidhya
AUGUST 4, 2019
Overview Singular Value Decomposition (SVD) is a common dimensionality reduction technique in data science We will discuss 5 must-know applications of SVD here and. The post Master Dimensionality Reduction with these 5 Must-Know Applications of Singular Value Decomposition (SVD) in Data Science appeared first on Analytics Vidhya.
Smart Data Collective
AUGUST 8, 2019
Big data is the lynchpin of new advances in cybersecurity. Unfortunately, predictive analytics and machine learning technology is a double-edged sword for cybersecurity. Hackers are also exploiting this technology, which means that there is a virtual arms race between cybersecurity companies and black hat cybercriminals. Datanami has talked about the ways that hackers use big data to coordinate attacks.
KDnuggets
AUGUST 7, 2019
Benford’s law is a little-known gem for data analytics. Learn about how this can be used for anomaly or fraud detection in scientific or technical publications.
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.
DataRobot
AUGUST 5, 2019
Comcast’s third annual PHLAI Conference - taking place on August 15th at the Comcast Technology Center in Philadelphia - will be focused around using artificial intelligence and machine learning to improve the customer experience. As the industry leader in machine learning, with hundreds of use cases focusing on improving the customer experience across all industries, DataRobot was invited to present at the conference, with a session led by Gourab De, DataRobot’s VP of Data Science.
IBM Big Data Hub
AUGUST 8, 2019
For the past nine years, Stack Overflow , a question-and-answer website for programmers, has polled developers to understand what technologies they are using and to find out what technologies they want to work with next. This year, the nearly 90,000 survey participants revealed that, once again, Python has risen in the ranks of language popularity.
Smart Data Collective
AUGUST 9, 2019
It’s no secret that everything businesses need to grow and accomplish their vision is theirs for the taking. But like anything that yields powerful results, the process doesn’t come easy. This describes the dilemma many organizations are facing when it comes to getting insights out of data. But before enterprises can shore up their analytics processes, they need to understand what’s holding them back.
KDnuggets
AUGUST 6, 2019
In this story, we’re going to take an aerial tour of optimization with Lagrange multipliers. When do we need them? Whenever we have an optimization problem with constraints.
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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.
Sisense
AUGUST 7, 2019
Blog. Building an effective dashboard according to best practices for dashboard design is the culmination of a comprehensive BI process that would usually include gathering requirements, defining KPIs, and creating a data model. However, the importance of proper dashboard design should not be understated — poorly designed dashboards could fail to convey useful information and insights and even make the data less comprehensible than it was originally.
TDAN
AUGUST 6, 2019
Deep learning, as defined by MathWorks, is a system of artificial intelligence that is built around learning by example. Multiple industries have already understood the benefits that deep learning brings to their operational capabilities. Deep learning is best demonstrated by the implementation of the technology in self-driving cars, as well as medical research to detect […].
Smart Data Collective
AUGUST 9, 2019
Big data in the gaming industry has played a phenomenal role in the field. We have previously talked about the benefits of using big data by gaming providers that offer cash games, such as slots. However, more mainstream games use big data as well. Fortnite is one of the games that uses big data to offer great service to its customers. Even Forbes Tech Council has written about the benefits of data lakes in Fortnite.
KDnuggets
AUGUST 6, 2019
Feature selection is one of the most important tasks in machine learning. Learn how to use a simple random search in Python to get good results in less time.
Speaker: Jay Allardyce, Deepak Vittal, Terrence Sheflin, and Mahyar Ghasemali
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.
Teradata
AUGUST 6, 2019
Digital transformation & regulatory requirements have long challenged Banks. Teradata has deep experience in ushering them through the transformation process.
IBM Big Data Hub
AUGUST 9, 2019
Introducing IBM StoredIQ Instascan for accelerated compliance and risk assessments. Read to learn more.
Smart Data Collective
AUGUST 7, 2019
We have talked extensively about the fields that rely most heavily on big data. The insurance industry is one of the companies investing the most in big data technology. Exactly one year ago today, SNS Telecom & IT published a report highlighting the demand for big data in the insurance industry. The report showed that insurers spent $2.4 billion on big data in 2018 alone.
KDnuggets
AUGUST 7, 2019
There are dozens of machine learning algorithms out there. It is impossible to learn all their mechanics; however, many algorithms sprout from the most established algorithms, e.g. ordinary least squares, gradient boosting, support vector machines, tree-based algorithms and neural networks.
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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