Sat.Mar 23, 2019 - Fri.Mar 29, 2019

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16 OpenCV Functions to Start your Computer Vision journey (with Python code)

Analytics Vidhya

Introduction Computer vision is among the hottest fields in any industry right now. It is thriving thanks to the rapid advances in technology and. The post 16 OpenCV Functions to Start your Computer Vision journey (with Python code) appeared first on Analytics Vidhya.

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Embedded Analytics Provide Meaningful Insights

David Menninger's Analyst Perspectives

Analytics and business intelligence (BI) play an instrumental role in enabling an organization’s business units and IT to utilize its data in both tactical and strategic ways to perform optimally. To accomplish this, organizations must not only access the data, generate and apply insights from analytics, and communicate the results, they also must ensure that the analytics are presented in a way that leads to action.

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Highlights from the Strata Data Conference in San Francisco 2019

O'Reilly on Data

Watch highlights from expert talks covering AI, machine learning, data analytics, and more. People from across the data world are coming together in San Francisco for the Strata Data Conference. Below you'll find links to highlights from the event. The journey to the data-driven enterprise from the edge to AI. Amy O'Connor explains how Cloudera applies an "edge to AI" approach to collect, process, and analyze data.

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Snowflake : Executive's Guide to Alternative Data Analytics

Corinium

Investment managers are expected to spend more than $1.6 billion on alternative data sets in 2020. The sheer volume of data produced will necessitate a change in how businesses acquire, process, and use it. Identifying and acquiring data sets is only the beginning of an investment firm’s data strategy. The key will be the ability to integrate a broad range of custom data sets, to share them flexibly, and to extract key insights in time.

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Generative AI Deep Dive: Advancing from Proof of Concept to Production

Speaker: Maher Hanafi, VP of Engineering at Betterworks & Tony Karrer, CTO at Aggregage

Executive leaders and board members are pushing their teams to adopt Generative AI to gain a competitive edge, save money, and otherwise take advantage of the promise of this new era of artificial intelligence. There's no question that it is challenging to figure out where to focus and how to advance when it’s a new field that is evolving everyday. 💡 This new webinar featuring Maher Hanafi, VP of Engineering at Betterworks, will explore a practical framework to transform Generative AI pr

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Nuts and Bolts of Reinforcement Learning: Introduction to Temporal Difference (TD) Learning

Analytics Vidhya

Introduction Q-learning became a household name in data science when DeepMind came up with an algorithm that reached superhuman levels on ATARI games. It’s. The post Nuts and Bolts of Reinforcement Learning: Introduction to Temporal Difference (TD) Learning appeared first on Analytics Vidhya.

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Salesforce Enlists Einstein to Bolster Its Analytics Muscle

David Menninger's Analyst Perspectives

I am happy to offer some insights on Salesforce.com 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.

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Seize The Power Of Customer Data Management – Best Practices

datapine

“Get closer than ever to your customers. So close that you tell them what they need well before they realize it themselves.” – Steve Jobs. We’re living in the midst of the age of information, a time when online data analysis can determine the direction and cement the success of a business or a startup that decides to dig deeper into consumer behavior insights.

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How to Achieve Consistent Quality in AI

DataRobot

AI has tremendous potential for benefiting humanity in every area of how we live and work. While most people realize this fact, their hopes for AI also come with a note of caution. A recent survey reported that 77% of Americans expressed that AI would have a “very positive” or “mostly positive” impact on how people work and live in the next 10 years.

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From enterprise to edge: embeddable databases unleash new capabilities

IBM Big Data Hub

IBM announced Informix V14.10 at Think 2019, revealing a host of new capabilities to clients and partners in attendance. Now, after beta testing with more than 25 customers and partners, it is available to the public.

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AI and cryptography: Challenges and opportunities

O'Reilly on Data

Shafi Goldwasser explains why the next frontier of cryptography will help establish safe machine learning. Continue reading AI and cryptography: Challenges and opportunities.

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Leading the Development of Profitable and Sustainable Products

Speaker: Jason Tanner

While growth of software-enabled solutions generates momentum, growth alone is not enough to ensure sustainability. The probability of success dramatically improves with early planning for profitability. A sustainable business model contains a system of interrelated choices made not once but over time. Join this webinar for an iterative approach to ensuring solution, economic and relationship sustainability.

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Data Lakes on Cloud & it’s Usage in Healthcare

BizAcuity

Data lakes are centralized repositories that can store all structured and unstructured data at any desired scale. Data can be stored as-is, without first structuring it, and different types of analytics can be run on it, from dashboards and visualizations to big data processing, real-time analytics, and machine learning to improve decision making. The power of the data lake lies in the fact that it often is a cost-effective way to store data.

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How Financial Institutions Are Becoming Champions Of Big Data

Smart Data Collective

If someone asked you which industry is the most innovative , you probably wouldn’t say the financial industry. In fact, that would probably be the last industry on your list. Nonetheless, the financial industry is using big data more than ever. The success of both Fintech companies and traditional banks will hinge on their ability to leverage big data to its fullest potential.

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CCO Melbourne Sponsorship Material

Corinium

Zendesk :

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Data warehousing is not a use case

O'Reilly on Data

Google BigQuery co-creator Jordan Tigani shares his vision for where cloud-scale data analytics is heading. Continue reading Data warehousing is not a use case.

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Navigating the Future: Generative AI, Application Analytics, and Data

Generative AI is upending the way product developers & end-users alike are interacting with data. Despite the potential of AI, many are left with questions about the future of product development: How will AI impact my business and contribute to its success? What can product managers and developers expect in the future with the widespread adoption of AI?

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Forrester’s 2019 Business Intelligence Vendor Landscape

Boris Evelson

Information technology keeps moving forward at an ever increasing pace. Business Intelligence (BI) technology isn’t falling behind and keeps constantly evolving. Gone are the days when vendors categorized themselves as IT focused and enterprise scalable vs. business user focused BI platforms mostly going after departmental and line of business (LOB) use cases.

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Your Guide To Understanding Various Types of Data Masking

Smart Data Collective

“Google Search Reveals Community College Student’s Social Security Number.” While this may seem like a headline you would find on sites like The Onion , this is something that actually happened. This situation occurred when staff members at a community college started to test a new type of online application that utilized files full of sensitive and unaltered data on a server that was not secure.

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How to infuse automation with data governance to thrive in a regulated world

IBM Big Data Hub

IIRA is an AI-powered regulatory on-ramp which helps businesses comply with a variety of regulations, and is available as an add-on to IBM Cloud Private for Data (ICP for Data).

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Scoring your business in the AI matrix

O'Reilly on Data

Jed Dougherty plots AI examples on a matrix to clarify the various interpretations of AI. Continue reading Scoring your business in the AI matrix.

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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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Ruthlessly Practical: Turning Busy Work into Brain Work for Your Data Science Team

DataRobot

Data scientist time is a precious, expensive commodity. Do you truly understand what your data science talent works on all day? Are they spending way too much time researching data science theory, coding the same data preparation tasks over and over again, and maintaining scripts for model factories? Take a serious look at what your data scientists actually do.

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Optimizing the IoT Infrastructure for Enhanced Big Data Performance

Smart Data Collective

The Internet of Things is one of the most groundbreaking trends affecting consumers and businesses all over the world. According to a report by Gartner, the economic impact of all products connected to the IoT will exceed $300 billion by next year. A number of factors are contributing to the proliferation of the IoT. One of the most influential changes is the increasing capacity of big data.

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The Role of Data and Reason in being Data-Driven

Andrew White

It’s all the rage- we need to be ‘data driven’. Unfortunately important ideas and advice are often dumbed-down or simplified to singular messages for ease of consumption and this can lead to yet more problems. To be data driven is a great example. What is such a thing? Conceptually to be data driven sounds like a situation whereby a decision ought to have its roots founded in data.

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Winners of the Strata Data Awards 2019

O'Reilly on Data

The Strata Data Award is given to the most disruptive startup, the most innovative industry technology, the most impactful data science project, and the most notable open source contribution. Continue reading Winners of the Strata Data Awards 2019.

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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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NLP Learning Series: Part 4 - Transfer Learning Intuition for Text Classification

MLWhiz

This post is the fourth 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.

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Big Data is Transforming the Future of WordPress Hosting

Smart Data Collective

Forbes contributor Kalev Leetaru recently wrote a fantastic article about the intersection of big data and website hosting. Leetaru notes that big data and cloud technology have led to the evolution of web hosting services. Cloud technology is changing the logistics of many traditional hosting plans. WordPress hosting is a prime example. How Big Data is Changing the Future of WordPress.

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Predicting Taxi Fares in New York Using Machine Learning in Real-Time

Dataiku

Do you remember the days before Uber, Lyft, or Gett? Standing in the street trying to hail a taxi waiting for the moment a free cab might drive by and spot you? These days that world seems so far away. And you might often wonder: how do these apps work? After all, that set price is not a random guess.

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Hacking the vote: The neuropolitical universe

O'Reilly on Data

Elizabeth Svoboda explains how biosensors and predictive analytics are being applied by political campaigns and what they mean for the future of free and fair elections. Continue reading Hacking the vote: The neuropolitical universe.

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How To Get Promoted In Product Management

Speaker: John Mansour

If you're looking to advance your career in product management, there are more options than just climbing the management ladder. Join our upcoming webinar to learn about highly rewarding career paths that don't involve management responsibilities. We'll cover both career tracks and provide tips on how to position yourself for success in the one that's right for you.

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AutoML for Data Augmentation

Insight

DeepAugment is an AutoML tool focusing on data augmentation. It utilizes Bayesian optimization for discovering data augmentation strategies tailored to your image dataset. The main benefits and features of DeepAugment are: Reduces the error rate of CNN models (showed 60% decrease in error for CIFAR10 on WRN-28–10) Saves time by automating the process 50 times faster than Google’s previous solution– AutoAugment The finished package is on PyPI.

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7 Ways Big Data Is Essential For Life Insurance Settlements

Smart Data Collective

The life insurance industry will soon undergo a dramatic transformation in response to advances in big data. A growing number of digital startups are starting to emphasize the impact of big data in this antiquated business. A number of insurance executives have been reluctant to embrace the changes of big data. One study found that 74% of respondents felt that the insurance industry had done an inadequate job addressing the need for big data.

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Tips for Successful Data Science Implementation in Insurance

Decision Management Solutions

Nancy Casbarro and Deb Zawisa of Novarico recently published a new paper on Data Science in Insurance: Expansion and Key Issues subscription required) that was summarized in this nice little article on Dig-in 3 challenges facing insurers in data science implementation. These three challenges – getting business buy in, attracting talent, and strategic alignment are exactly what we see in our work with insurers.

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Likewar: How social media is changing the world and how the world is changing social media.

O'Reilly on Data

Peter Singer explores the new rules of power in the age of social media and how we can navigate a world increasingly shaped by "likes" and lies. Continue reading Likewar: How social media is changing the world and how the world is changing social media.

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How Embedded Analytics Gets You to Market Faster with a SAAS Offering

Start-ups & SMBs launching products quickly must bundle dashboards, reports, & self-service analytics into apps. Customers expect rapid value from your product (time-to-value), data security, and access to advanced capabilities. Traditional Business Intelligence (BI) tools can provide valuable data analysis capabilities, but they have a barrier to entry that can stop small and midsize businesses from capitalizing on them.