Analytics Vidhya
MARCH 27, 2019
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.
O'Reilly on Data
MARCH 27, 2019
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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David Menninger's Analyst Perspectives
MARCH 25, 2019
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.
Corinium
MARCH 27, 2019
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.
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.
Analytics Vidhya
MARCH 24, 2019
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.
O'Reilly on Data
MARCH 28, 2019
Lauren Kunze discusses lessons learned from an analysis of interactions between humans and chatbots. Continue reading Chatting with machines: Strange things 60 billion bot logs say about human nature.
Data Leaders Brief brings together the best content for data, strategy, and BI professionals from the widest variety of industry thought leaders.
datapine
MARCH 27, 2019
“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.
DataRobot
MARCH 29, 2019
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.
O'Reilly on Data
MARCH 27, 2019
Shafi Goldwasser explains why the next frontier of cryptography will help establish safe machine learning. Continue reading AI and cryptography: Challenges and opportunities.
BizAcuity
MARCH 29, 2019
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.
Speaker: Aarushi Kansal, AI Leader & Author and Tony Karrer, Founder & CTO at Aggregage
Software leaders who are building applications based on Large Language Models (LLMs) often find it a challenge to achieve reliability. It’s no surprise given the non-deterministic nature of LLMs. To effectively create reliable LLM-based (often with RAG) applications, extensive testing and evaluation processes are crucial. This often ends up involving meticulous adjustments to prompts.
IBM Big Data Hub
MARCH 26, 2019
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.
O'Reilly on Data
MARCH 28, 2019
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.
Smart Data Collective
MARCH 28, 2019
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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Are you trying to decide which entity resolution capabilities you need? It can be confusing to determine which features are most important for your project. And sometimes key features are overlooked. Get the Entity Resolution Evaluation Checklist to make sure you’ve thought of everything to make your project a success! The list was created by Senzing’s team of leading entity resolution experts, based on their real-world experience.
Boris Evelson
MARCH 26, 2019
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.
DataRobot
MARCH 25, 2019
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.
O'Reilly on Data
MARCH 27, 2019
Jed Dougherty plots AI examples on a matrix to clarify the various interpretations of AI. Continue reading Scoring your business in the AI matrix.
Smart Data Collective
MARCH 27, 2019
“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.
Speaker: Nicholas Zeisler, CX Strategist & Fractional CXO
The first step in a successful Customer Experience endeavor (or for that matter, any business proposition) is to find out what’s wrong. If you can’t identify it, you can’t fix it! 💡 That’s where the Voice of the Customer (VoC) comes in. Today, far too many brands do VoC simply because that’s what they think they’re supposed to do; that’s what all their competitors do.
IBM Big Data Hub
MARCH 25, 2019
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).
Andrew White
MARCH 28, 2019
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.
O'Reilly on Data
MARCH 28, 2019
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.
Smart Data Collective
MARCH 28, 2019
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.
Speaker: Margaret-Ann Seger, Head of Product, Statsig
Experimentation is often seen as an aspirational practice, especially at smaller, fast-moving companies who are strapped for time and resources. So, how can you get your team making decisions in a more data-driven way while continuing to remain lean and maintaining ship velocity? In this webinar, Margaret-Ann Seger, Head of Product at Statsig, will teach you how to build an experimentation culture from the ground-up, graduating from just getting started with data-driven development to operating
MLWhiz
MARCH 29, 2019
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.
Dataiku
MARCH 28, 2019
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.
O'Reilly on Data
MARCH 28, 2019
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.
Smart Data Collective
MARCH 26, 2019
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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“Reimagined: Building Products with Generative AI” is an extensive guide for integrating generative AI into product strategy and careers featuring over 150 real-world examples, 30 case studies, and 20+ frameworks, and endorsed by over 20 leading AI and product executives, inventors, entrepreneurs, and researchers.
Insight
MARCH 27, 2019
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.
Decision Management Solutions
MARCH 25, 2019
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.
O'Reilly on Data
MARCH 28, 2019
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.
Smart Data Collective
MARCH 28, 2019
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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Think your customers will pay more for data visualizations in your application? Five years ago, they may have. But today, dashboards and visualizations have become table stakes. Turning analytics into a source of revenue means integrating advanced features in unique, hard-to-steal ways. Download this white paper to discover which features will differentiate your application and maximize the ROI of your analytics.
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