Goto

Collaborating Authors

Top 67 software for Text Analysis, Text Mining, Text Analytics in 2017

@machinelearnbot

Top software for Text Analysis, Text Mining, Text Analytics: Text Analysis, Text Mining, Text Analytics uses statistical pattern learning to find patterns and trends from text data.


People

#artificialintelligence

Problem decomposition and theory reformulation, integrated cognitive architectures for autonomous robots, distributed constraint satisfaction problems, semigroup theory and dynamical systems, category theory in software design. Interests include machine learning, approximation algorithms, on-line algorithms and planning systems. Calvin, William H. – Theoretical neurophysiologist and author of "The Cerebral Code", and "How Brains Think". Gesture and narrative language, animated agents, intonation, facial expression, computer vision. Intersection of computer science and game theory, computer science and economics, multiagent systems, automated negotiation and contracting.


10 Common NLP Terms Explained for the Text Mining Novice

@machinelearnbot

If you're relatively new to the Natural Language Processing and Text Mining 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" from your LDA we've got you covered. The terms we chose were based on terms we often find ourselves explaining to users and customers on a day to day basis. Natural Language Processing (NLP) - A Computer Science field connected to Artificial Intelligence and Computational Linguistics which focuses on interactions between computers and human language and a machine's ability to understand, or mimic the understanding of human language.


Text Mining in Python: Steps and Examples

#artificialintelligence

In today's world, according to the industry estimates only 20 percent of the data in the structured format is being generated as we speak as we tweet as we send messages on What's App, email, Facebook, Instagram or any text messages. And, the majority of this data exists in the textual form which is highly unstructured format, in order to produce meaningful insights from the text data then we need to access a method called Text Analysis. Text Mining is the process of deriving meaningful information from natural language text. Natural Language Processing(NLP) is a part of computer science and artificial intelligence which deals with human languages. In other words, NLP is a component of text mining that performs a special kind of linguistic analysis that essentially helps a machine "read" text.


Best 19 Free Data Mining Tools

@machinelearnbot

It is rightfully said that data is money in today's world. Along with the transition to an app-based world comes the exponential growth of data. However, most of the data is unstructured and hence it takes a process and method to extract useful information from the data and transform it into understandable and usable form. Data mining or "Knowledge Discovery in Databases" is the process of discovering patterns in large data sets with artificial intelligence, machine learning, statistics, and database systems. Free data mining tools ranges from complete model development environments such as Knime and Orange, to a variety of libraries written in Java, C and most often in Python.