Analytics Vidhya
MAY 9, 2019
This article was submitted as part of Analytics Vidhya’s Internship Challenge. Introduction “What are the different branches of analytics?” Most of us, when we’re. The post A Practical Introduction to Prescriptive Analytics (with Case Study in R) appeared first on Analytics Vidhya.
Dataconomy
MAY 10, 2019
Breaking down the workforce options for AI developers to structure raw data for machine learning. Here is a look. While it may seem like artificial intelligence (AI) has hit the big time, a lot of work needs to be done before its potential really come to life. In our modern. The post The Right Workforce Turns Data into Rocket Fuel for AI Projects appeared first on Dataconomy.
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Smart Data Collective
MAY 8, 2019
If you’re a marketer or business owner in today’s competitive marketplace, you’ve probably tried just about everything you can think of to maximize your success. You’ve dabbled in digital marketing, visited trade shows, paid for print advertising, and incentivized customer testimonials. It’s probably resulted in lots of stress, sleepless nights, and CBD oil drops to give you the energy and focus to keep going.
Data Science 101
MAY 6, 2019
Sponsored Post by T.J. DeGroat of Springboard. At Springboard , we recently sat down with Michael Beaumier, a data scientist at Google, to discuss his transition into the field, what the interview process is like, the future of data wrangling, and the advice he has for aspiring data professionals. The full video Q&A is below, but here are some of the highlights.
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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?
Analytics Vidhya
MAY 5, 2019
Introduction “How did your neural network produce this result?” This question has sent many data scientists into a tizzy. It’s easy to explain how. The post A Guide to Understanding Convolutional Neural Networks (CNNs) using Visualization appeared first on Analytics Vidhya.
Dataconomy
MAY 9, 2019
Digital transformation dominates most CIO priority lists pertaining to questions such as: How will digital transformation affect IT infrastructure? Will technology live on-premise or in the cloud? Depending on where that data lives, an organization requires different skill sets. If you’re building these resources in-house, then you need an infrastructure.
Data Science Current brings together the best content for data science professionals from the widest variety of thought leaders.
Eugene Yan
MAY 10, 2019
OMSCS CS7646 (Machine Learning for Trading) - Don't sell your house to trade algorithmically.
Analytics Vidhya
MAY 7, 2019
Introduction I love descriptive statistics. Visualizing data and analyzing trends is one of the most exciting aspects of any data science project. But what. The post Extracting and Analyzing 1000 Basketball Games using Pandas and Chartify appeared first on Analytics Vidhya.
Dataconomy
MAY 6, 2019
How to implement an anonymous data collection scheme that allows the manufacturer to anonymously collect data from its end devices without knowing exactly which device it came from? Yes, this is one of the challenges for the second Blockchain Hackathon (part of LongHash Cryptocon Vol2) in Berlin on May 18-19. The post “With prol?iferatio?n of digitized technologies, the public is becoming aware of data-collecting sensors & it’s concerns” ?
Smart Data Collective
MAY 7, 2019
We have published a number of glowing articles on the benefits of big data in the world of marketing. However, many of these tutorials focus on the general benefits of big data, rather than specific, data-driven marketing strategies. One of the ways that big data is transforming local marketing is by optimizing Google Reviews. We were pleased to hear from Michael Del Gigante, the CEO of MDG Advertising.
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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.
DataRobot
MAY 7, 2019
As more and more companies rely on AI , people are questioning whether or not AI can be trusted. Business reputations are damaged when inscrutable black box AI systems make mistakes or make biased decisions. To avoid these issues, organizations are seeking out ways to apply best practices of AI governance to ensure that AIs are following business rules and making sensible and trustworthy decisions.
DataRobot Blog
MAY 7, 2019
by Jen Underwood. Artificial intelligence (AI) and machine learning can deliver unprecedented value to the business. Unfortunately, fantastic findings often get lost in translation. From expressing metrics in unfamiliar terminology to presenting odd. Read More.
Dataconomy
MAY 9, 2019
The era of everything-as-a-service (XaaS) has provided both an opportunity and a challenge for companies across industries. The XaaS model, a subscription-based solution that makes cloud-based applications available on demand unlike the traditional license-based platforms of the past, delivers several noteworthy advantages over its predecessors. Between cost reductions and easier.
Smart Data Collective
MAY 6, 2019
Big data is having a huge effect on the future of cryptocurrency markets around the world. A growing number of companies are leveraging big data to streamline cryptotrading and improve security and customer satisfaction. Big Data Made Simple wrote a very helpful post about the benefits of using big data to facilitate the cryptocurrency trading market.
Speaker: Scott Sehlhorst
We know we want to create products which our customers find to be valuable. Whether we label it as customer-centric or product-led depends on how long we've been doing product management. There are three challenges we face when doing this. The obvious challenge is figuring out what our users need; the non-obvious challenges are in creating a shared understanding of those needs and in sensing if what we're doing is meeting those needs.
DataRobot
MAY 9, 2019
Companies planning to be AI-driven will find pragmatic advice in Best Practices: Scaling Data Science Across The Enterprise , a report from industry analysts at Forrester Research. Author Kjell Carlsson, Ph.D. identifies three key takeaways in the report: enterprises struggle to expand data science across the organization; without alignment, data science projects fail to drive outcomes; adopt five best practices to scale data science.
DataCentric podcast
MAY 9, 2019
Nutanix.NEXT hosted nearly 7,000 IT professionals -- Matt & Steve managed to get one to talk about his experiences deploying Nutanix HCI in an enterprise environment. Join hosts Matt Kimball, Steve McDowell as they talk to special guest Drew Harris, who is Vice President of IT Operations at the Cosmopolitan Casino in Las Vegas to hear about the reality of modern IT colliding with HCI.
DataRobot
MAY 10, 2019
How can you better understand the risks involved when funding a loan? With feature effects. Jordan Meyer, Customer-Facing Data Scientist at DataRobot , gives a quick explanation of how feature effects in DataRobot help manage loan risk. With feature effects, one feature is examined at a time while holding all other factors constant.
DataCentric podcast
MAY 8, 2019
Nutanix.NEXT 2019 kicks off in Anaheim CA, where nearly 7,000 IT professionals gather to hear Nutanix's vision of software-defined multi-cloud world. Included in that 7,000 are hosts Matt Kimball and Steve McDowell, analysts with Moor Insights & Strategy. Nutanix has become the dominant challenger in the software-defined datacenter world. That's not lost on Steve & Matt, who offer up their overall impressions of the event so far, the great energy surrounding.NEXT, and the ambitio
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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