Pickl AI

AUGUST 1, 2023

In this article, we will explore the concept of applied text mining in Python and how to do text mining in Python. Introduction to Applied Text Mining in Python Before going ahead, it is important to understand, What is Text Mining in Python?

Data Analysis 52

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Lexalytics

MAY 25, 2021

One of the most important and most-used functions in text analytics and NLP is sentiment analysis — the process of determining whether a word, phrase, or document is positive, negative, or neutral. Once content has been hand-sorted, we set our algorithms free to learn to differentiate the two.

Natural Language Processing 52

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Marktechpost

JULY 17, 2023

It relates to employing algorithms to find and examine data patterns to forecast future events. In a word, artificial intelligence is the general term for machine learning and predictive analytics. Machine learning and deep learning models are two major categories of predictive algorithms.

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ODSC - Open Data Science

SEPTEMBER 19, 2024

Streamlining Government Regulatory Responses with Natural Language Processing, GenAI, and Text Analytics Through text analytics, linguistic rules are used to identify and refine how each unique statement aligns with a different aspect of the regulation.

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Pickl AI

JULY 23, 2023

It requires sophisticated tools and algorithms to derive meaningful patterns and trends from the sheer magnitude of data. Real-time data feeds and algorithmic trading strategies have transformed the dynamics of financial markets. It helps automate complex data analysis tasks, recognise patterns, and make accurate predictions.

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Bitext

SEPTEMBER 17, 2021

Recapping, the main limitation of Machine Learning for text analytics is that it is “blind” to text structure. And text structure is essential for moving towards text understanding. This is the first benefit Linguistics provides to data sicentists.

Machine Learning 52

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ODSC - Open Data Science

FEBRUARY 17, 2023

How Text Analytics and AI Can Help Investigators Combat Human Trafficking Assessing large quantities of narrative data for patterns using manual analysis alone can be time-consuming and produces limited qualitative results.

ML 52

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Pickl AI

JULY 20, 2023

Predictive Analytics Projects: Predictive analytics involves using historical data to predict future events or outcomes. Techniques like regression analysis, time series forecasting, and machine learning algorithms are used to predict customer behavior, sales trends, equipment failure, and more.

Big Data 40

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Analytics Vidhya

JUNE 16, 2021

The post How to Perform Basic Text Analysis without Training Dataset appeared first on Analytics Vidhya. ArticleVideo Book This article was published as a part of the Data Science Blogathon Overview This article will give you a basic understanding of how.

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Lexalytics

APRIL 5, 2021

This would change in 1986 with the publication of “Parallel Distributed Processing” [ 6 ], which included a description of the backpropagation algorithm [ 7 ]. In retrospect, this algorithm seems obvious, and perhaps it was. We were definitely in a Kuhnian pre-paradigmatic period. It would not be the last time that happened.)

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Kavita Ganesan

AUGUST 25, 2022

AI algorithms must understand the subtle meanings in text and nuances in expressions, analyze the cultural context, and then determine whether it’s offensive without incorrectly penalizing harmless content. The volume of AI-based hate speech removal on Facebook. This is what one of my clients did.

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Mlearning.ai

FEBRUARY 27, 2023

Thus, this class is supposed to handle all pre-processing to transform data from the raw form to the precise form a machine learning algorithm expects. Thus, it is necessary to vectorize the review texts in this class.

Data Science 52

Data Science Python Deep Learning Text Analytics 52

Unite.AI

NOVEMBER 6, 2024

We then took this technology to local Cambridge, Massachusetts schools and elicited the help of local teenagers to train their algorithms, which allowed us to capture more nuance in the algorithms than previously possible. What are the key innovations and algorithms that enable Pienso's no-code interface for building AI models?

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LevelAI

FEBRUARY 5, 2024

Organizations can delve deeper by utilizing sophisticated text analytics tools, identifying recurring themes, trends, and even specific language patterns within interactions. Many issues go unnoticed and unfixed. Quantifying the Qualitative: Customer service data extends beyond mere sentiment analysis.

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Explosion

FEBRUARY 14, 2016

If you were doing text analytics in 2015, you were probably using word2vec. We used Gensim, and trained the model using the Skip-Gram with Negative Sampling algorithm, using a frequency threshold of 10 and 5 iterations. Sense2vec (Trask et.

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