ODSC - Open Data Science

FEBRUARY 17, 2023

What to Expect in 2023: A Data Scientist’s Top 5 AI Predictions Between improved NLP and increased use of AI in finance, here are one data scientist’s 2023 AI predictions. Here’s how you can uncover actionable textual and geospatial patterns related to counter human trafficking using NLP. Here’s why that may or may not be true.

ML 52

ML ChatGPT Data Science Machine Learning 52

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

Big Data Natural Language Processing Machine Learning Python 40

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

Machine Learning Big Data Text Analytics Chatbots 52

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. Recommeded Reading 7 NLP Applications in Business List of Common AI Problem Types in Business

NLP 52

NLP Text Analytics Artificial Intelligence Artificial Intelligence 52

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.

Data Science 276

Data Science Text Analytics Algorithm NLP 276

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.

Data Analysis 52

Data Analysis Explainability Algorithm Natural Language Processing 52

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.)

Neural Network 52

Neural Network Convolutional Neural Networks Natural Language Processing BERT 52

Explosion

FEBRUARY 14, 2016

If you were doing text analytics in 2015, you were probably using word2vec. Sense2vec: Using NLP annotations for more precise vectors The idea behind sense2vec is super simple. def transform_texts(texts): # Load the annotation models nlp = English() # Stream texts through the models. Sense2vec (Trask et.

Natural Language Processing 40

Natural Language Processing NLP Text Analytics Explainability 40