Analytics Vidhya
MARCH 7, 2019
This article has been updated on Women’s Day, 2019. Introduction This women’s day, we at Analytics Vidhya are celebrating the power of women in. The post 29 Inspiring Women Blazing a Trail in the Data Science World appeared first on Analytics Vidhya.
O'Reilly on Data
MARCH 7, 2019
NLP systems in health care are hard—they require broad general and medical knowledge, must handle a large variety of inputs, and need to understand context. We’re in an exciting decade for natural language processing (NLP). Computers will get as good as humans in complex tasks like reading comprehension, language translation, and creative writing.
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David Menninger's Analyst Perspectives
MARCH 8, 2019
I am happy to share some insight on Domo drawn from our latest Value Index research, which provides an analytic representation of our assessment of how well vendors’ offerings meet buyers’ requirements. The Ventana Research Value Index: Analytics and Business Intelligence 2019 is the distillation of a year of market and product research efforts by Ventana Research.
IBM Big Data Hub
MARCH 7, 2019
Success with AI models depends on achieving success with collecting and organizing your data, then analyzing the data to make smarter business decisions.
Advertiser: ZoomInfo
AI adoption is reshaping sales and marketing. But is it delivering real results? We surveyed 1,000+ GTM professionals to find out. The data is clear: AI users report 47% higher productivity and an average of 12 hours saved per week. But leaders say mainstream AI tools still fall short on accuracy and business impact. Download the full report today to see how AI is being used — and where go-to-market professionals think there are gaps and opportunities.
Analytics Vidhya
MARCH 5, 2019
Introduction The rapid rise of data science as a professional field has lured in people from all backgrounds. Engineers, computer scientists, marketing and finance. The post 11 Steps to Transition into Data Science (for Reporting / MIS / BI Professionals) appeared first on Analytics Vidhya.
Data Science 101
MARCH 7, 2019
Read to the end to learn more about a new study group I will be launching. In Late January 2019, Microsoft launched 3 new certifications aimed at Data Scientists/Engineers. For a while, Microsoft has been toying with different methods for training and credentials. They launched the Microsoft Professional Program in Data Science back in 2017. While it provides great content, it did not result in either a college diploma or an official Microsoft certification.
Data Leaders Brief brings together the best content for data, strategy, and BI professionals from the widest variety of industry thought leaders.
IBM Big Data Hub
MARCH 6, 2019
Leveraging IBM cloud and partnered with IBM leaders, Sonoma County transformed with data and Watson AI.
Analytics Vidhya
MARCH 6, 2019
Introduction Machine learning is disrupting multiple and diverse industries right now. One of the biggest industries to be impacted – finance. Functions like fraud. The post Hands-On Introduction to creditR: An Amazing R Package to Enhance Credit Risk Scoring and Validation appeared first on Analytics Vidhya.
Sisense
MARCH 7, 2019
Despite progress in recent years, UNESCO says that more girls than boys remain out of school. In fact, according to the UNESCO Institute for Statistics , “16 million girls will never set foot in a classroom – and women account for two-thirds of the 750 million adults without basic literacy skills.”. There’s a widely-known African proverb that says “If you educate a man, you educate an individual.
MLWhiz
MARCH 8, 2019
This post is the third post of the NLP Text classification series. To give you a recap, I started up with an NLP text classification competition on Kaggle called Quora Question insincerity challenge. So I thought to share the knowledge via a series of blog posts on text classification. The first post talked about the different preprocessing techniques that work with Deep learning models and increasing embeddings coverage.
Speaker: Ben Epstein, Stealth Founder & CTO | Tony Karrer, Founder & CTO, Aggregage
When tasked with building a fundamentally new product line with deeper insights than previously achievable for a high-value client, Ben Epstein and his team faced a significant challenge: how to harness LLMs to produce consistent, high-accuracy outputs at scale. In this new session, Ben will share how he and his team engineered a system (based on proven software engineering approaches) that employs reproducible test variations (via temperature 0 and fixed seeds), and enables non-LLM evaluation m
IBM Big Data Hub
MARCH 8, 2019
The IBM Hybrid Data Management Platform provides simplicity and control in one package for your hybrid architecture needs or journey to the cloud.
Analytics Vidhya
MARCH 6, 2019
Introduction “People underestimate how complex intelligence is.” How close are we to Artificial General Intelligence (AGI)? It seems we take a step closer to. The post DataHack Radio #19: The Path to Artificial General Intelligence with Professor Melanie Mitchell appeared first on Analytics Vidhya.
Jet Global
MARCH 5, 2019
One of the most common manual reporting interventions users of Microsoft Dynamics NAV, GP, and 365 Business Central makes is financial report consolidations – whether it’s across multiple companies, departments, or other dimensions. But with Jet Reports, you can do this automagically! Instead of wasting one more hour, or risking one more reporting error with copying, pasting, exporting, and labor-intensive composition for multi-company or multi-department reports, attend this month’s Success Ser
Data Science 101
MARCH 6, 2019
University can be a great way to learn data science. However, many universities are very expensive, difficult to get admitted, or not geographically feasible. Luckily, a few of them are willing to share data science, machine learning and deep learning materials online for everyone. Here is just I small list I have come across lately. MIT Deep Learning – Lecture notes, slides and guest talks about deep learning and self driving cars Introduction to Artificial Intelligence from UC Berkeley &
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The DHS compliance audit clock is ticking on Zero Trust. Government agencies can no longer ignore or delay their Zero Trust initiatives. During this virtual panel discussion—featuring Kelly Fuller Gordon, Founder and CEO of RisX, Chris Wild, Zero Trust subject matter expert at Zermount, Inc., and Principal of Cybersecurity Practice at Eliassen Group, Trey Gannon—you’ll gain a detailed understanding of the Federal Zero Trust mandate, its requirements, milestones, and deadlines.
John Wheeler
MARCH 6, 2019
It has been 5 years since Gartner embarked on the journey to enhance our coverage of the risk management technology marketplace. That journey included in-depth survey research and countless interactions with our end-user clients to understand their need to better manage strategic, operational and IT/cybersecurity risks. These end-user needs and resulting demand led to the definition of a new technology marketplace – integrated risk management (IRM).
Sisense
MARCH 6, 2019
Every year there’s high anticipation to see what key message Gartner will present in the yearly Data & Analytics Summits. The BI industry takes Gartner’s perspective very seriously, and year after year, it’s very common to see messages that were first described in the Gartner summits making their way into the websites of many analytics vendors.
IBM Big Data Hub
MARCH 7, 2019
Bring our unified POV on Data Replication and its impact on driving analytics initiatives to counter Qlik buying Attunity. .
Data Science 101
MARCH 2, 2019
A new community for data visualization professionals has launched. It is called the Data Visualization Society. According to the website, The Data Visualization Society aims to collect and establish best practices and foster community to support its members as they develop their data visualization skills. Currently, membership is free and they are looking for help growing the community.
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GAP's AI-Driven QA Accelerators revolutionize software testing by automating repetitive tasks and enhancing test coverage. From generating test cases and Cypress code to AI-powered code reviews and detailed defect reports, our platform streamlines QA processes, saving time and resources. Accelerate API testing with Pytest-based cases and boost accuracy while reducing human error.
Jet Global
MARCH 5, 2019
With all the attention being paid to artificial intelligence (AI) these days, it’s no surprise that enterprise leaders are scrambling to find ways to shoehorn AI implementations into their technology stack. But when you ask leaders in the enterprise to define what they’re looking for from AI, their answers frequently focus on solutions that will empower better business decision making.
BizAcuity
MARCH 8, 2019
Workforce Analytics – What is its need for companies. Workforce Analytics in simple terms can be defined as an advanced set of software and methodology tools that measures, characterizes, and organizes sophisticated employee data and these tools helps in understanding the employee performance in a logical way. Human resource leaders are using workforce analytics under various forms such as predictive and prescriptive analytics.
IBM Big Data Hub
MARCH 5, 2019
Instead of choosing between multiple download options, anyone can now download and use a single, full-featured version of Db2 for as long as they want, without paying fees, contacting an IBM sales person, providing a credit card, getting on a mailing list or enduring adware.
DataRobot
MARCH 5, 2019
In a previous blog post , we introduced you to Zach Deane-Mayer, a data scientist who runs our core modeling team. One of the most important tools in his team’s arsenal is a data science performance evaluation system created and maintained by our QA team. This system is at the core of our comprehensive testing philosophy that we believe is crucial to delivering a platform that our customers can trust, no matter what DataRobot features they’re using or how they’ve chosen to deploy them.
Advertiser: ZoomInfo
ZoomInfo customers aren’t just selling — they’re winning. Revenue teams using our Go-To-Market Intelligence platform grew pipeline by 32%, increased deal sizes by 40%, and booked 55% more meetings. Download this report to see what 11,000+ customers say about our Go-To-Market Intelligence platform and how it impacts their bottom line. The data speaks for itself!
Insight
MARCH 5, 2019
Ad recommendations should be understandable to the individual consumer, but is it possible to increase interpretability without sacrificing accuracy? Internet of Thing (AWS IoT) Are you looking to transition into the field of machine learning in Silicon Valley, New York, or Toronto? Apply for the upcoming June session today ( Deadline is March 25th for SV and NYC ) or learn more about the Artificial Intelligence program at Insight!
Data Science 101
MARCH 4, 2019
Brandon Rohrer (along with others ) created an excellent resource for academic programs, Industry recommendations for academic data science programs. The resource is authored by a number of industry data scientists and university faculty. It is collection of useful information for college data science programs. Here are some of the topics: What do Industry data scientists do?
Teradata
MARCH 7, 2019
Teradata CEO Oliver Ratzesberger celebrates International Women's Day.
Sisense
MARCH 4, 2019
The world of data is now the world of Big Data. The genie is out of the bottle and there’s no going back. We produce more and more data every day and the datasets being generated are getting more and more complex. Traditionally, the way to handle this has been to scale up computing resources to handle these bigger datasets. That’s not feasible for the long term on a global scale, nor is it tenable in the near term for smaller organizations who may have limited resources to deal with their analyt
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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.
Decision Management Solutions
MARCH 4, 2019
Machine learning is the scientific study of algorithms and statistical models that computer systems use to effectively perform a specific task without using explicit instructions, relying on models and inference instead. It is seen as a subset of artificial intelligence. — Wikipedia. Machine Learning is increasingly widely used to make predictions.
DataRobot
MARCH 4, 2019
Can You Trust That Your AI Was Built Correctly? It has been more than three years since the last time I competed in a data science competition, and yet there’s one memory about that competition that remains vivid in my mind. I had spent a busy week at my computer coding up a cool-looking solution, and I was ready to submit my first entry to the competition.
bridgei2i
MARCH 8, 2019
If we are not actively engaged in industries related to technology, we may fail to fully appreciate how we might already be influenced by artificial intelligence in our day-to-day world. Everyone is talking about self-driving cars, seemingly inanimate objects conversing with you about your personal preferences, someone somewhere already seems to recommend your shopping list armed with the knowledge of what you like or dislike.
Sisense
MARCH 4, 2019
Data Dictionaries. Sounds like a blast from the past, right? Wrong. This simple, long-standing tool is even more relevant to us today than it ever was in the past. Working with data people every day, I know what it takes for our analysts and data engineers to go through the data and make it easier to analyze (it’s a known fact that 80% of their time is spent preparing and managing data for analysis).
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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?
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