1. Articles from dzone.com

  2. 25-48 of 149 « 1 2 3 4 5 6 7 »
    1. Don’t Fear New Technology: The Future Moves Fast Big Data

      Don’t Fear New Technology: The Future Moves Fast Big Data

      At Return Path, I work on a data science team that uses machine learning and natural language processing to produce features that augment data feeds that we sell directly to clients. Return Path’s core business is in email marketing optimization. In a nutshell, we use data and analytics to help marketers optimize how and when they’re sending emails to their customers. While this is Return Path’s core business, I work in a division of the company that focuses on consumer insight data.

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    2. An Introduction to Implementing Neural Networks Using TensorFlow AI

      If you have been following the world of data science/machine learning, you just can’t miss the buzz around deep learning and neural networks. Organizations are looking for people with deep learning skills wherever they can use them. From running competitions to open-sourcing projects and paying big bonuses, people are trying every possible thing to tap into this limited pool of talent.

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      Mentions: CSV Matlab
    3. Big Dataset: Analyzing All Reddit Comments With ClickHouse Big Data

      Big Dataset: Analyzing All Reddit Comments With ClickHouse Big Data

      In this blog, I'll use ClickHouse and Tabix to look at a new very large dataset for research. It is hard to come across interesting datasets, especially a big one (and by big, I mean one billion rows or more). Before, I've used on-time airline performance available from Bureau of Transporation Statistics . Another recent example is NYC taxi and Uber trips data , with over one billion records.

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      Mentions: Amazon MySQL
    4. Providing Decision Support to Hospitals Across Multiple EHR Systems AI

      Providing Decision Support to Hospitals Across Multiple EHR Systems AI

      It's beyond doubt that data is increasingly important in healthcare, but there is also a strong sense that doctors themselves are not very keen on it. I wrote last year , for instance, about a study exploring how doctors felt when patients brought their own data into consultations. "We've heard doctors say more and more that people bring this data into the clinic and they're just overwhelmed by it.

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      Mentions: MIT CSAIL EHR
    5. Machine Learning and Analytics in IT Ops AI

      Machine Learning and Analytics in IT Ops AI

      Though current ticket data investigation and reporting practices employed by enterprises can usually obtain statistics and information on ticket count, ownership, categories, severities, etc., they fall behind when it comes to abstracting and comprehending the treasure of information concealed in the text comments of ticket data. This is precisely where IT ops analytics (ITOA) — using big data, machine learning, and natural language processing (NLP) techniques — is gaining momentum.

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      Mentions: Oracle NLP SME
    6. Serverless and Chatbots: Made for Each Other AI

      Serverless and Chatbots: Made for Each Other AI

      According to Forrester Research, “globally, 57% of companies either use chatbots already, or plan to do so in the coming year.” That’s incredible! Experts think that the use of chatbots is only going to explode in near future. Think about it. Chatbots have been around for quite a long time. But why this sudden surge and interest in chatbots now ? Well, there are various reasons. Unlike the earlier days, many AI and NLP capabilities are now available as consumable services.

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    7. Introduction to Deepnets AI

      Introduction to Deepnets AI

      Deepnets are a new resource brought to the BigML platform. On October 5, 2017, Deepnets will be available via the BigML Dashboard, API, and WhizzML . Deepnets (an optimized version of deep neural networks) are part of a broader family of classification and regression methods based on learning data representations from a wide variety of data types (i.e. numeric, categorical, text, image).

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    8. NLP Tutorial Using Python NLTK (Simple Examples) AI

      NLP Tutorial Using Python NLTK (Simple Examples) AI

      Find out how AI-Fueled APIs from Neura can make interesting products more exciting and engaging. In this post, we will talk about natural language processing (NLP) using Python. This NLP tutorial will use the Python NLTK library. NLTK is a popular Python library which is used for NLP. So what is NLP? And what are the benefits of learning NLP? Put simply, natural language processing (NLP) is about developing applications and services that are able to understand human languages.

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      Mentions: Brazil Lancaster NLP
    9. Chatbots Aren't Really That Great AI

      Chatbots Aren't Really That Great AI

      Chatbots are the new "it" things in technology today. They're computer programs that are designed to carry out conversations with users via text or speech. Famous bots like Alexa, Siri, Google Assistant, and Facebook Messenger are beginning to represent the next big computational platform. Bots are user-friendly, they afford tremendous opportunities for actionable insights, and they are ever-evolving, ever-learning, ever in beta. So why aren’t they able to deliver on their promises?

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    10. Artificial Intelligence, Communication, and the Evolution of Software Testing AI

      Artificial Intelligence, Communication, and the Evolution of Software Testing AI

      Artificial Intelligence, Communication, and the Evolution of Software Testing DZone's Guide to Artificial Intelligence, Communication, and the Evolution of Software Testing Learn about the intersection of artificial intelligence, Agile, and DevOps from software testing and QA luminary Isabel Evans. by Sep. 16, 17 · AI Zone Free Resource Find out how AI-Fueled APIs from Neura can make interesting products more exciting and engaging.

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    11. How Do I Get More Insights From Metadata? AI

      How Do I Get More Insights From Metadata? AI

      It was great talking to Aaron Kalb, Co-Founder and Head of Product at Alation — an enterprise collaborative data platform that’s using artificial intelligence (AI) and machine learning (ML) to find information of value and insights in metadata. Q: What are the keys to getting information of value from metadata? A: Start by getting a handle on all of your data assets. A lot of companies don’t realize where all of their data resides.

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      Mentions: PII
    12. Chatbots With Machine Learning: Building Neural Conversational Agents AI

      Chatbots With Machine Learning: Building Neural Conversational Agents AI

      Twenty-two. And you? Me too! Wow! Note the (end-of-sequence)token at the end of each sentence in the batch. This special token helps neural networks understand sentence bounds and update their internal state wisely. Some models may use additional meta information from data such as speaker ID, gender, emotion, etc. Now, we are ready to move on to discussing generative models.

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    13. Apple's HomePod: What's in It for Developers? IoT

      Apple's HomePod: What's in It for Developers? IoT

      Join For Free Discover why Bluetooth mesh is the next evolution of IoT solutions. Download the mesh overview . With only a few days to go for the iPhone event, the buzz around it this year is greater than what it was a few years ago. With the WWDC event done, we can expect something radical from the technology giant. While we were privy to most of the iOS features that would be incorporated into the iPhone 8, geeks and developers are eagerly waiting for the phone's release.

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    14. A Brief Guide to Chatbot Architecture AI

      A Brief Guide to Chatbot Architecture AI

      Humans always seem to be fascinated with self-operating devices and these days, it is human-like and automated chatbots that are of interest. The combination of immediate response and constant connectivity makes them an enticing way to extend or replace the trend of web applications. But how do these automated programs work? Let’s take a look. How Do Chatbots Actually Work? Chatbots work by adopting three classification methods. 1.

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      Mentions: Bayes NLP
    15. What are the Best Practices for a Successful Bot Development Project? AI

      What are the Best Practices for a Successful Bot Development Project? AI

      If you are planning to develop a chatbot, you might be wondering what things to take into consideration before embarking on a development project. Many developers may ask, "What is the strategy for successful chatbot development and its best practices?" Here are some of the best practices to lead you to a successful chatbot development project. Know Your Audience First of all, building a successful bot requires some deep understanding of the customer’s product or services and its user base.

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      Mentions: Microsoft
    16. How Influential Businesses Like Google Use AI and What We Can Learn AI

      How Influential Businesses Like Google Use AI and What We Can Learn AI

      AI is a hot buzzword right now, and businesses of all shapes and sizes are trying to find a way to leverage its power for their own particular needs. Exciting, futuristic, and vaguely science-fictiony, AI is currently seen as a must-have tool for turbocharging one’s business and improving the quality of customer experience. It’s been a game changer for enterprise companies like Google, Microsoft, Amazon, and IBM who have the computing power and resources to access field experts.

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    17. How to Build a Pizza-Delivering Bot With Mule, Slack, API.AI, and NLP in Minutes AI

      Is it possible to create a fully functional conversational bot with natural language processing (NLP) in minutes? Good news — it is! In this post, we will show you how to start from the ground up, giving you everything you need to create your own basic conversational bot using 100% free accounts and software (yes, all this is all powered for free).

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      Mentions: API
    18. Chatbots and AI: The Fintech Trends to Watch Mobile

      Chatbots and AI: The Fintech Trends to Watch Mobile

      Fintech is a lucrative yet quite saturated market. In order to stay competitive, businesses should keep track of the emerging trends and be able to capitalize on them before their competitors do. Artificial intelligence is currently among the most promising fintech trends. Leading financial brands such as Capital One, MasterCard, as well as hundreds of startups have set the pace for the adoption of virtual financial advisors.

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    19. How to Use Artificial Intelligence to Make Your Marketing Smarter Developer Marketing

      How to Use Artificial Intelligence to Make Your Marketing Smarter Developer Marketing

      How to Use Artificial Intelligence to Make Your Marketing Smarter DZone's Guide to How to Use Artificial Intelligence to Make Your Marketing Smarter Take a look at two of the most exciting emerging AI technologies for marketers today! by Aug. 23, 17 · Developer Marketing Zone Free Resource Join For Free These days you can collect swathes of information about your intended audience from just about any source.

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    20. 3 Ways AI and IoT Bring Data Analytics Insights to Life Big Data

      3 Ways AI and IoT Bring Data Analytics Insights to Life Big Data

      3 Ways AI and IoT Bring Data Analytics Insights to Life DZone's Guide to 3 Ways AI and IoT Bring Data Analytics Insights to Life We believe that natural language processing (NLP), which allows us to talk to machines as if they were human, is the future (and the present) of business intelligence. by Aug. 16, 17 · Big Data Zone Free Resource Join For Free Leveraging big data is necessary for survival.

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      Mentions: Canada NLP IoT
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