Unite.AI

FEBRUARY 19, 2024

To elucidate the aforementioned conundrum, this article aims to analyze the current state-of-art of RPA and examine the converging impact of Artificial Intelligence (AI) and Machine Learning (ML) technologies. Machine learning-based anomaly detection and RPA-enhanced fraud detection systems have proven effective.

Neural Network 176

Neural Network Natural Language Processing Automation Robotics 176

NLP People

MAY 18, 2018

Are you looking to study or work in the field of NLP? For this series, NLP People will be taking a closer look at the NLP education & development landscape in different parts of the world, including the best sites for job-seekers and where you can go for the leading NLP-related education programs on offer.

NLP 52

NLP Computational Linguistics Data Mining Natural Language Processing 52

IBM Journey to AI blog

AUGUST 28, 2023

What is text mining? Text mining —also called text data mining—is an advanced discipline within data science that uses natural language processing (NLP) , artificial intelligence (AI) and machine learning models, and data mining techniques to derive pertinent qualitative information from unstructured text data.

Data Mining 170

Data Mining Convolutional Neural Networks Categorization Machine Learning 170

Chatbots Life

MARCH 16, 2023

The field of machine learning has been around for over 60 years and has been used to solve some of the most complex problems companies have ever faced. One area in which machine learning can have a dramatic positive impact is through call center data collection. What Is Call Center Data and How to Analyze It?

Machine Learning 52

Machine Learning Text Analytics Natural Language Processing Business Intelligence 52

DataRobot Blog

MARCH 9, 2022

This is one of the reasons why detecting sentiment from natural language (NLP or natural language processing ) is a surprisingly complex task. The Sentiment140 Dataset provides valuable data for training sentiment models to work with social media posts and other informal text. It provides 1.6 Sentiment analysis, a baseline method.

Machine Learning 52

Machine Learning Neural Network Convolutional Neural Networks Deep Learning 52

Lexalytics

SEPTEMBER 9, 2021

For nearly two decades, Lexalytics has been a pioneer in structured and unstructured data analytics, translating text into profitable decisions with our natural language processing (NLP), machine learning (ML), and artificial intelligence (AI) solutions for the world’s most customer-centric brands.

Natural Language Processing 52

Natural Language Processing Machine Learning Text Analytics NLP 52

ODSC - Open Data Science

MAY 9, 2024

Designed for robust text analytics and generation, DBRX excels in information retrieval, text summarization, machine translation, conversational AI, and content creation. Whether you’re managing data pipelines or deploying machine learning models, Thunder makes the process smooth and efficient.

AI Tools 52

AI Tools Large Language Models Machine Learning Data Science 52

Bitext

SEPTEMBER 17, 2021

In previous posts, we have outlined the crucial role of Machine Learning for Analytics (in How to Make Machine Learning more Effective using Linguistic Analysis? ) , and the implications of using Machine Learning for analyzing and structuring text (in How Phrase Structure helps Machine Learning ? ).

Machine Learning 52

Machine Learning Text Analytics Big Data Chatbots 52

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

ODSC - Open Data Science

OCTOBER 23, 2023

In the world of artificial intelligence and machine learning, this evolution has been nothing short of remarkable. Traditionally, our NLP track has focused on the usual aspects of NLP, such as text analytics and sentiment analysis. This is especially true of the last 12 months.

Large Language Models 52

Large Language Models Prompt Engineer Prompt Engineering Data Science 52

Pickl AI

AUGUST 1, 2023

Introduction to Applied Text Mining in Python Before going ahead, it is important to understand, What is Text Mining in Python? Text mining is also known as text analytics or Natural Language Processing (NLP). It helps in discovering hidden patterns and organizing text data into meaningful clusters.

Data Analysis 52

Data Analysis Python Categorization Data Mining 52

LevelAI

FEBRUARY 5, 2024

Text Analytics: Spotting occurrences of words This approach matches pre-defined keywords or sequences of words to text excerpts within call transcripts. A text analytics solution would be able to match the name of the company to verify if the agent has said, “Hello, this is Level AI customer service.

Automation 52

Automation Text Analytics Natural Language Processing Generative AI 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

Pickl AI

JULY 23, 2023

Examples of unstructured data include text files, images, audio, and video content. While unstructured data may seem chaotic, advancements in artificial intelligence and machine learning enable us to extract valuable insights from this data type. This step is crucial for eliminating inconsistencies and ensuring data integrity.

Data Analysis 52

Data Analysis Explainability Algorithm Machine Learning 52

Lexalytics

APRIL 5, 2021

Fast-forward a couple of decades: I was (and still am) working at Lexalytics, a text-analytics company that has a comprehensive NLP stack developed over many years. The graph below shows the trend of publications in machine learning. So, whatever did happen to neural networks?

Neural Network 52

Neural Network Convolutional Neural Networks Natural Language Processing BERT 52