Dataversity

SEPTEMBER 27, 2021

Natural Language Processing (NLP) has been on the rise for several years, and for good reason. Click to learn more about author Ben Lorica. With the ability to identify new variants of COVID-19, improve customer service, and significantly refine search capabilities, use cases are expanding as the technology proliferates.

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Data Science Dojo

OCTOBER 10, 2023

Role of AI for leading professionals Here are some specific examples of how attending AI events and conferences can help individuals and organizations to learn and adapt to new technologies: A software engineer can gain knowledge about the latest advancements in natural language processing by attending an AI conference.

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Pickl AI

DECEMBER 25, 2024

By understanding its significance, readers can grasp how it empowers advancements in AI and contributes to cutting-edge innovation in natural language processing. Its diverse content includes academic papers, web data, books, and code. Frequently Asked Questions What is the Pile dataset?

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Data Science Dojo

SEPTEMBER 20, 2023

The pretraining data predominantly comprises publicly available data, with some contributions from research papers and social media conversations. Significance of Falcon AI The performance of Large Language Models is intrinsically linked to the data they are trained on, making data quality crucial.

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Pickl AI

NOVEMBER 24, 2024

Denoising Autoencoders (DAEs) Denoising autoencoders are trained on corrupted versions of the input data. The model learns to reconstruct the original data from this noisy input, making them effective for tasks like image denoising and signal processing. They help improve data quality by filtering out noise.

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ODSC - Open Data Science

JUNE 29, 2023

Let’s download the dataframe with: import pandas as pd df_target = pd.read_parquet("[link] /Listings/airbnb_listings_target.parquet") Let’s simulate a scenario where we want to assert the quality of a batch of production data. These constraints operate on top of statistical summaries of data, rather than on the raw data itself.

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Towards AI

JUNE 12, 2024

Word embedding is a technique in natural language processing (NLP) where words are represented as vectors in a continuous vector space. This focus on understanding context is similar to the way YData Fabric, a data quality platform designed for data […] The story starts with word embedding.

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O'Reilly Media

NOVEMBER 19, 2024

For example, a mention of “NLP” might refer to natural language processing in one context or neural linguistic programming in another. A generalized, unbundled workflow A more accountable approach to GraphRAG is to unbundle the process of knowledge graph construction, paying special attention to data quality.

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Pickl AI

MARCH 4, 2025

Unlike traditional AI, which operates within predefined rules and tasks, It uses advanced technologies like Machine Learning, Natural Language Processing (NLP) , and Large Language Models (LLMs) to navigate complex, dynamic environments. For example, a chatbot that understands user sentiment and intent through NLP.

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Dataconomy

MARCH 27, 2023

Some of the ways in which ML can be used in process automation include the following: Predictive analytics:  ML algorithms can be used to predict future outcomes based on historical data, enabling organizations to make better decisions. How can RPA improve data quality and streamline data management processes?

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AWS Machine Learning Blog

FEBRUARY 21, 2025

Rajesh Nedunuri is a Senior Data Engineer within the Amazon Worldwide Returns and ReCommerce Data Services team. He specializes in designing, building, and optimizing large-scale data solutions.

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Flipboard

JULY 4, 2023

Advantages of vector databases Spatial Indexing – Vector databases use spatial indexing techniques like R-trees and Quad-trees to enable data retrieval based on geographical relationships, such as proximity and confinement, which makes vector databases better than other databases.

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Data Science Dojo

MARCH 18, 2024

Retrieval-augmented generation (RAG) brings an approach to natural language processing that’s both smart and efficient. Reprocess the data Before your LLM can start learning from this task-specific data, the data must be processed into a format the model understands. Why use RAG?

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Dataconomy

SEPTEMBER 4, 2023

Text analytics: Text analytics, also known as text mining, deals with unstructured text data, such as customer reviews, social media comments, or documents. It uses natural language processing (NLP) techniques to extract valuable insights from textual data.

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Dataconomy

MAY 9, 2023

Another example of AI in accounting is the use of natural language processing (NLP) technology to automate data entry and categorization. NLP can extract relevant information from unstructured data sources such as invoices, receipts, and emails, and classify them into appropriate accounting categories.

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The MLOps Blog

JUNE 27, 2023

Learn more The Best Tools, Libraries, Frameworks and Methodologies that ML Teams Actually Use – Things We Learned from 41 ML Startups [ROUNDUP] Key use cases and/or user journeys Identify the main business problems and the data scientist’s needs that you want to solve with ML, and choose a tool that can handle them effectively.

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Data Science Connect

JULY 24, 2023

These chatbots use natural language processing (NLP) algorithms to understand user queries and offer relevant solutions. Data Quality and Privacy Concerns: AI models require high-quality data for training and accurate decision-making.

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Precisely

AUGUST 29, 2024

Key Takeaways Data quality ensures your data is accurate, complete, reliable, and up to date – powering AI conclusions that reduce costs and increase revenue and compliance. Data observability continuously monitors data pipelines and alerts you to errors and anomalies. What does “quality” data mean, exactly?

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Towards AI

MAY 20, 2023

Challenges of building custom LLMs Building custom Large Language Models (LLMs) presents an array of challenges to organizations that can be broadly categorized under data, technical, ethical, and resource-related issues. Ensuring data quality during collection is also important.

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Smart Data Collective

SEPTEMBER 22, 2021

The next aspect to addressing unstructured data is extracting more concrete information from it, and this may be the most complicated element. How do you quantify unstructured data? Once businesses can see “inside” their unstructured data, there’s a lot to explore.

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Data Science Connect

JULY 28, 2023

This data is then integrated into centralized databases for further processing and analysis. Data Cleaning and Preprocessing IoT data can be noisy, incomplete, and inconsistent. Data engineers employ data cleaning and preprocessing techniques to ensure data quality, making it ready for analysis and decision-making.

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Dataconomy

JULY 6, 2023

Have a niche skillset Given the shortage of skilled AI professionals, companies should build a team with expertise in AI technologies, including machine learning, natural language processing, computer vision, and ethics.

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Dataconomy

MARCH 13, 2023

With advances in machine learning, deep learning, and natural language processing, the possibilities of what we can create with AI are limitless. However, the process of creating AI can seem daunting to those who are unfamiliar with the technicalities involved. How to improve your data quality in four steps?

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Precisely

MARCH 7, 2024

Insurance industry leaders are just beginning to understand the value that generative AI can bring to the claims management process. By harnessing the power of machine learning and natural language processing, sophisticated systems can analyze and prioritize claims with unprecedented efficiency and timeliness.

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Towards AI

FEBRUARY 20, 2024

If you want an overview of the Machine Learning Process, it can be categorized into 3 wide buckets: Collection of Data: Collection of Relevant data is key for building a Machine learning model. It isn't easy to collect a good amount of quality data.

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Google Research AI blog

MARCH 30, 2023

Towards this goal, we are introducing DataPerf , a set of new data-centric ML challenges to advance the state-of-the-art in data selection, preparation, and acquisition technologies, designed and built through a broad collaboration across industry and academia.

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Women in Big Data

DECEMBER 13, 2023

The Bay Area Chapter of Women in Big Data (WiBD) hosted its second successful episode on the NLP (Natural Language Processing), Tools, Technologies and Career opportunities. Computational Linguistics is rule based modeling of natural languages. The event was part of the chapter’s technical talk series 2023.

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Pickl AI

AUGUST 29, 2024

Scalability : It can handle large datasets efficiently, as the model can be trained on existing data without the need for continuous human intervention. Disadvantages Data Quality: Passive learning relies heavily on the quality and diversity of the pre-collected data.

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IBM Journey to AI blog

DECEMBER 16, 2022

An enterprise data catalog does all that a library inventory system does – namely streamlining data discovery and access across data sources – and a lot more. For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance.

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Dataconomy

AUGUST 7, 2023

Unstructured data includes text, images, audio, video, and other data types that don’t neatly fit into rows and columns. In AI applications, unstructured data can be vital for tasks such as natural language processing, image recognition, and sentiment analysis.

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AWS Machine Learning Blog

NOVEMBER 1, 2024

Fine-tuning is a powerful approach in natural language processing (NLP) and generative AI , allowing businesses to tailor pre-trained large language models (LLMs) for specific tasks. This process involves updating the model’s weights to improve its performance on targeted applications.

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Becoming Human

MAY 19, 2023

Chatbots, along with conversational AI , can provide customer support, handle customer queries, and even process transactions. AI chatbots can understand human language and respond naturally using natural language processing (NLP). This makes them ideal for customer support applications.

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Heartbeat

AUGUST 23, 2023

But what if there was a technique to quickly and accurately solve this language puzzle? Enter Natural Language Processing (NLP) and its transformational power. But what if there was a way to unravel this language puzzle swiftly and accurately?

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Pickl AI

JULY 12, 2024

Neural networks are inspired by the structure of the human brain, and they are able to learn complex patterns in data. Deep Learning has been used to achieve state-of-the-art results in a variety of tasks, including image recognition, Natural Language Processing, and speech recognition.

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Pickl AI

DECEMBER 25, 2024

Descriptive analytics is a fundamental method that summarizes past data using tools like Excel or SQL to generate reports. Techniques such as data cleansing, aggregation, and trend analysis play a critical role in ensuring data quality and relevance.

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Pickl AI

OCTOBER 17, 2023

Learn how Data Scientists use ChatGPT, a potent OpenAI language model, to improve their operations. ChatGPT is essential in the domains of natural language processing, modeling, data analysis, data cleaning, and data visualization. Let’s examine some Data Analysis Plugins of ChatGPT.

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Dataconomy

MARCH 27, 2023

Some of the ways in which ML can be used in process automation include the following: Predictive analytics:  ML algorithms can be used to predict future outcomes based on historical data, enabling organizations to make better decisions. How can RPA improve data quality and streamline data management processes?

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