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All Blog Posts Tagged 'NLP' (26)

Topic detection

Introduction to topic model:

In machine learning and natural language processing, a topic model is a type of statistical model for discovering the abstract "topics" that occur in a collection of documents. Topic modeling is a frequently used text-mining tool for discovery of hidden semantic structures in a text body. 

In topic modeling, a topic is defined by a cluster of words with each word in the cluster having a probability of occurrence for the given topic, …

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Added by fatma gadelrab on March 31, 2019 at 10:06am — No Comments

The Coming Revolution in Recurrent Neural Nets (RNNs)

Summary: Recurrent Neural Nets (RNNs) are at the core of the most common AI applications in use today but we are rapidly recognizing broad time series problem types where they don’t fit well.  Several alternatives are already in use and one that’s just been introduced, ODE net is a radical departure from our way of thinking about the solution.

 …

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Added by William Vorhies on March 11, 2019 at 7:43am — No Comments

Your Guide to Natural Language Processing (NLP)

How machines process and understand human language



Everything we express (either verbally or in written) carries huge amounts of information. The topic we choose, our tone, our selection of words, everything adds some type of information that can be interpreted and value extracted from it. In theory, we can understand and even predict human behaviour using that information.…

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Added by Diego Lopez Yse on January 18, 2019 at 3:46am — No Comments

How I used NLP (Spacy) to screen Data Science Resumes

Resume making is very tricky. A candidate has many dilemmas,

  • whether to state a project at length or just mention the bare minimum
  • whether to mention many skills or just mention his/her core competency skill…
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Added by Venkat Raman on January 15, 2019 at 2:30am — 1 Comment

Comparison of the Text Distance Metrics

Measuring the similarity between texts is a common task in many applications. It is useful in classic NLP fields like search, as well as in such far from NLP areas as medicine and genetics. There are many different approaches of how to compare two texts (strings of characters). Each has its own advantages and disadvantages and is good only…

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Added by Igor Bobriakov on January 4, 2019 at 12:30am — No Comments

Getting Started with NLP: Simple Topic Modeling in R (Part 1)

What is NLP?

Natural Language Processing (NLP) can be simply defined as teaching an algorithm to read and analyze human (natural) languages just like the human brain does, but a lot faster than a human could, more accurately and on very large amounts of data.

It is a great skill to have if you are an aspiring data scientist or data analyst because has…

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Added by Aymone Kouame on August 11, 2018 at 2:00pm — No Comments

Articulate - Open source platform for build conversational interfaces with intelligent agents

Articulate is an open source project that will allow you to take control of you conversational interfaces, without being worried where and how your data is stored. Also, Articulate is built with an user-centered design where the main goal is to make experts and beginners feel comfortable when building their intelligent agents.

The main features of Articulate are:

  • Open source project
  • Based on…
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Added by Daniel Calvo-Marin on July 2, 2018 at 7:00pm — No Comments

AI-Driven Transformation & the Impact on Marketing

Around two decades ago, marketing existed as a soft function within organizations. There is no denying its importance, of course, but from an organizational perspective, it was a function hard to measure in terms of impact on the bottom-line. But then boomed the digital age, and with it, an advent of channels…

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Added by Senthil Nathan R on July 1, 2018 at 11:30pm — No Comments

Steps required before adopting AI & Cognitive Computing platform

Enterprises are learning fast about the relevance and use of AI and Cognitive Computing platforms. Before adopting AI and Cognitive Computing platforms, enterprises must focus on designing the right strategy for their business. A data-driven strategy is very important to derive the maximum benefit from the…

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Added by Dileep Srinivasan on May 2, 2018 at 5:30pm — 1 Comment

Temporal Convolutional Nets (TCNs) Take Over from RNNs for NLP Predictions

Summary: Our starting assumption that sequence problems (language, speech, and others) are the natural domain of RNNs is being challenged.  Temporal Convolutional Nets (TCNs) which are our workhorse CNNs with a few new features are outperforming RNNs on major applications today.  Looks like RNNs may well be history.

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Added by William Vorhies on May 1, 2018 at 7:29am — 1 Comment

Natural Language Understanding (NLU) in Fraud Risk Management – a case study

I.  Introduction

This is a continuation of my previous blog, “Natural Language Understanding – Application Notes with Context Discriminant”. 

Background:

Natural Language Understanding (NLU) is a subtopic of Natural Language Processing (NLP). Successful implementations of NLU are difficult because of limitations in prevailing technology. SiteFocus solved these limitations with a new approach to NLU. This approach has been successfully…

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Added by Sing Koo on April 10, 2018 at 1:30pm — 1 Comment

Data or Algorithms – Which is More Important?

Summary:  Which is more important, the data or the algorithms?  This chicken and egg question led me to realize that it’s the data, and specifically the way we store and process the data that has dominated data science over the last 10 years.  And it all leads back to Hadoop.

 …

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Added by William Vorhies on November 28, 2017 at 10:36am — 1 Comment

Recommender Engine - Under The Hood

Many of us are bombarded with various recommendations in our day to day life, be it on e-commerce sites or social media sites. Some of the recommendations look relevant but some create range of emotions in people, varying from confusion to anger.

There are basically two types of recommender systems, Content based and Collaborative filtering. Both have their pros and cons depending upon the…

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Added by Venkat Raman on November 22, 2017 at 10:00pm — No Comments

Under the Hood With Chatbots

Summary:  This is the second in our chatbot series.  Here we explore Natural Language Understanding (NLU), the front end of all chatbots.  We’ll discuss the programming necessary to build rules based chatbots and then look at the use of deep learning algorithms that are the basis for AI enabled chatbots.

 …

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Added by William Vorhies on November 14, 2017 at 10:30am — 4 Comments

Beginners Guide to Chatbots

Summary:  This is the first in a series about Chatbots.  In this first installment we cover the basics including their brief technological history, uses, basic design choices, and where deep learning comes into play.  In subsequent articles we’ll describe in more detail about how they are actually programmed and best practice dos and don’ts.

 

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Added by William Vorhies on November 7, 2017 at 1:30pm — 2 Comments

Natural Language Understanding (NLU) in Enterprise – Digesting IPO Prospectus

Introduction

Business ventures based on existing or disruptive business models taking on the route of Initial Public Offering are always a challenge to investors who want to profit from early investment into those would be “unicorn IPO”. A good investment may get worse before it gets better. Others may get worse and never recover. Aside from the macroeconomics and consumer trends that could affect the outcome of such investments, the fundamentals of these new public offerings…

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Added by Sing Koo on October 31, 2017 at 2:30am — No Comments

Natural Language Understanding – Application Notes with Context Discriminant

Introduction

Deep Learning can be used to automate just about every repetitive task that is currently or formerly performed by humans. Factory robots, autonomous cars, Internet of Things are example of these automations. Yet, mentally challenging tasks such as conducting research or strategic planning with natural language textual documents remain a daunting task for automation. We look into the root cause of this challenge and have implemented a solution to automate these…

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Added by Sing Koo on October 6, 2017 at 1:00pm — No Comments

Introducing Context Discriminant - Artificial Intelligence for Tactical Strategic Execution with Bionic Fusion

Background
 

Prevailing AI technology for analytics prefer the use of statistical science as the foundation for machine learning (ML) on historical data to distill knowledge and experience. Whether it be supervised or unsupervised, the result is then incorporated into playback engines to analyze new data. These methods and procedures work well for predictable scenarios with known outcomes and known variables.

 

What if the variables are unknown, and…

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Added by Sing Koo on May 19, 2017 at 9:00am — No Comments

10 Common NLP Terms Explained for the Text Analysis Novice

If you’re relatively new to the NLP and Text Analysis world, you’ll more than likely have come across some pretty technical terms and acronyms, that are challenging to get your head around, especially, if you’re relying on scientific definitions for a plain and simple explanation.

We decided to put together a list of 10 common terms in Natural Language Processing which we’ve broken down in layman terms, making them easier to understand. So if you don’t know your “Bag of Words”…

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Added by Mike Waldron on January 17, 2017 at 1:30am — 1 Comment

The Emerging World of Neural Net Driven MT

Originally posted here, where you can see all the graphics

There has been much in the news lately about the next wave of MT technology driven by a technology called deep learning and neural nets (DNN). I will attempt to provide a brief layman’s overview about what this is, even though I am barely qualified to do this (but if Trump can run for POTUS then…

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Added by Kirti Vashee on July 29, 2016 at 9:30am — No Comments

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