Analytics Vidhya
JUNE 2, 2019
Introduction What would you do if you had the chance to pick the brains behind one of the most popular Natural Language Processing (NLP). The post DataHack Radio #23: Ines Montani and Matthew Honnibal – The Brains behind spaCy appeared first on Analytics Vidhya.
Dataconomy
JUNE 4, 2019
Here is how CIOs can use AIOps to create a strategy and foundation for the digital future. CIOs and operations teams across the globe are tuned into the rapidly developing area of AIOps (Artificial intelligence for IT operations). As Artificial Intelligence and Machine Learning continue to evolve and advance, IT. The post IT Automation – The Missing Piece in the AIOPS puzzle appeared first on Dataconomy.
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Machine Learning (Theory)
JUNE 7, 2019
The first is Sunday afternon during the Industry Expo day. This one is meant to be quite practical, starting with an overview of Contextual Bandits and leading into how to apply the new Personalizer service, the first service in the world functionally supporting general contextual bandit learning. The second is Friday morning. This one is more academic with many topics.
Smart Data Collective
JUNE 1, 2019
. Many bloggers get very frustrated after they have been working for a couple of months. They initially are excited about the possibility of making a six-figure stream of passive income. After they get started though, they discovered that the legwork can be overwhelming. The good news is that machine learning is making it much easier for them to create a successful blogging career, as Jeff Bullas points out.
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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
JUNE 3, 2019
“Sound does not travel in a vaccum.“ The above concept might just be a simple fact for you – but I had a tough. The post The AI Comic: Z.A.I.N – Issue #1: Automating Attendance using Computer Vision appeared first on Analytics Vidhya.
Dataconomy
JUNE 6, 2019
Today, customers globally want to buy bespoke goods, made within the time and delivered at the right place. The production of the future will be focused on the personalized market which will respond to the demand changes. How would this tendency affect the future of ERP software? Enterprise resource planning. The post What’s the Future of ERP software in a Fintech Niche?
Data Science Current brings together the best content for data science professionals from the widest variety of thought leaders.
Smart Data Collective
JUNE 1, 2019
Big Data is taking center stage, and it is touted as one of the most groundbreaking technologies of the present time. The utilization of Big Data is not only limited to only one sector anymore. Instead, Big Data is used in various different sectors. For example, Big Data analytics are used in various agricultural fields as well to derive useful insights in order to yield better crops.
DataRobot
JUNE 5, 2019
How can schools leverage data to ensure that every student has access to the educational resources they need? We spoke with two faculty members at Florida International University (FIU) to learn how they address this issue to successfully help at-risk students overcome obstacles in their academic careers.
Victor Zhou
JUNE 7, 2019
Information Gain, like Gini Impurity , is a metric used to train Decision Trees. Specifically, these metrics measure the quality of a split. For example, say we have the following data: The Dataset What if we made a split at x = 1.5 x = 1.5 x = 1. 5 ? An Imperfect Split This imperfect split breaks our dataset into these branches: Left branch, with 4 blues.
Depends on the Definition
JUNE 7, 2019
In the previous posts, we saw how to build strong and versatile named entity recognition systems and how to properly evaluate them. But often you want to understand your model beyond the metrics. So in this tutorial I will show you how you can build an explainable and interpretable NER system with keras and the LIME algorithm.
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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.
Smart Data Collective
JUNE 7, 2019
With today’s technology, there’s an increasing demand for stream processing. Data, for instance, has to be processed fast so that the companies can keep up to the changing business and market conditions in real time. This is where real-time stream processing enters the picture, and it may probably change everything you know about big data. Read this article as we’ll tackle what big data and stream processing are.
DataRobot
JUNE 3, 2019
Robotic process automation (RPA) is software that aims to automate back-office work, eliminating the need for humans to perform mundane tasks like gathering and sorting data and freeing up their time to do more strategic work. Artificial intelligence (AI) is a computer system that is able to perform tasks that ordinarily require human intelligence. When brought together, these two powerful tools take digital transformations to the next level.
DataCentric podcast
JUNE 3, 2019
This episode of the DataCentric Podcast has co-host Steve McDowell talking with Eric Herzog. Eric, a long-time veteran of the storage world, is the Chief Marketing Officer and VP WW Storage Channels for IBM Storage. In a wide-ranging conversation, Eric offers up IBM's vision of what's important in storage. Not to give away the game, but it's all about applications, workloads, and use-cases.
Analytics Vidhya
JUNE 5, 2019
Introduction If I had to pick one platform that has single-handedly kept me up-to-date with the latest developments in data science and machine learning. The post Top 7 Machine Learning Github Repositories for Data Scientists appeared first on Analytics Vidhya.
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.
Smart Data Collective
JUNE 7, 2019
Task management applications are changing the way we manage teams. Here are some of the primary benefits of these task management applications : Task management tools improve team productivity. Task management tools make sure that teams operate more efficiently. Task management tools minimize worker stress. Task management tools help with monitoring trends.
DataRobot
JUNE 4, 2019
Just six months after the inaugural DataRobot AI Experience London , the machine learning and artificial intelligence conference returned to the British capital on Wednesday, May 22nd. The event featured a substantially bigger audience, showing just how ascendant AI is for businesses across the globe. With a powerhouse lineup of DataRobot customers and users from Sky , Reckitt Benckiser , 118118Money , and PwC sharing their experience as AI-driven enterprises, the more than 400 attendees were ea
Smart Data Collective
JUNE 7, 2019
One of the most fascinating things about big data is its ability to optimize the design of products that have pre-dated digital technology by centuries. One of the most interesting examples is with magnets. Magnets are ancient devices. They are so old, that the history of their discovery has been lost in legend. It is rumored that the first magnet was discovered by a Cretan man named Magnes over 4000 years ago.
Smart Data Collective
JUNE 3, 2019
In a previous article I shared some of the challenges, benefits and trends of Big Data in the telecommunications industry. This time, I will focus on the financial services industry based on previous IBM studies in this industry and some personal experiences. An Industry Without Physical Products. Big Data’s promise of value in the financial services industry is particularly differentiating.
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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