KDnuggets

JUNE 18, 2025

Follow the installation process outlined in the documentation, and you will see a new tab in your Jupyter Notebook labeled Nbextensions. By using Python code, we can generate an interactive visualization that enables users to engage in a more intuitive data exploration process.

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Flipboard

JUNE 9, 2025

By Bala Priya C , KDnuggets Contributing Editor & Technical Content Specialist on June 9, 2025 in Python Image by Author | Ideogram Have you ever spent several hours on repetitive tasks that leave you feeling bored and… unproductive? But you can automate most of this boring stuff with Python. I totally get it. Let’s get started.

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Python Natural Language Processing Data Science Machine Learning 150

KDnuggets

JUNE 23, 2025

A project contains: Source code : The Python scripts or notebooks for training and evaluation. Example MLproject file: name: my_ml_project conda_env: conda.yaml entry_points: main: parameters: data_path: {type: str, default: "data.csv"} epochs: {type: int, default: 10} command: "python train.py --data_path {data_path} --epochs {epochs}" 3.

Machine Learning 227

Machine Learning Machine Learning Natural Language Processing Data Science 227

Data Science Dojo

NOVEMBER 18, 2024

With LangChain, a Requests Toolkit, and a ReAct agent, talking to your API with natural language is easier than ever. This blog post will walk you through the process of setting up and utilizing the Requests Toolkit with LangChain in Python. You can find more details about necessary headers in your API documentation.

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KDnuggets

JUNE 17, 2025

Step 4: Leverage NotebookLM’s Tools Audio Overview This feature converts your document, slides, or PDFs into a dynamic, podcast-style conversation with two AI hosts that summarize and connect key points. Study Guides & Briefing Docs In the “Studio” panel, you can generate structured outputs such as study guides or briefing documents.

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Natural Language Processing Data Science Machine Learning Machine Learning 276

Analytics Vidhya

JULY 27, 2024

This is where the term frequency-inverse document frequency (TF-IDF) technique in Natural Language Processing (NLP) comes into play. Introduction Understanding the significance of a word in a text is crucial for analyzing and interpreting large volumes of data. appeared first on Analytics Vidhya.

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Analytics Vidhya

NOVEMBER 7, 2023

Introduction In the ever-evolving field of natural language processing and artificial intelligence, the ability to extract valuable insights from unstructured data sources, like scientific PDFs, has become increasingly critical.

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Dataconomy

APRIL 21, 2025

Natural language processing (NLP) is a fascinating field at the intersection of computer science and linguistics, enabling machines to interpret and engage with human language. What is natural language processing (NLP)? Gensim: Focused on topic modeling to facilitate deep text analysis.

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Natural Language Processing Deep Learning Deep Learning Computer Science 91

Analytics Vidhya

JUNE 21, 2023

Introduction Transformers are revolutionizing natural language processing, providing accurate text representations by capturing word relationships. The adaptability of transformers makes these models invaluable for handling various document formats. Applications span industries like law, finance, and academia.

Python 290

Python Natural Language Processing Analytics Analytics 290

KDnuggets

JUNE 25, 2025

Blog Top Posts About Topics AI Career Advice Computer Vision Data Engineering Data Science Language Models Machine Learning MLOps NLP Programming Python SQL Datasets Events Resources Cheat Sheets Recommendations Tech Briefs Advertise Join Newsletter 10 FREE AI Tools That’ll Save You 10+ Hours a Week No tech skills needed.

Natural Language Processing 224

Natural Language Processing Data Science AI AI 224

KDnuggets

JUNE 17, 2025

By Abid Ali Awan , KDnuggets Assistant Editor on June 17, 2025 in Language Models Image by Author I was first introduced to Modal while participating in a Hugging Face Hackathon, and I was genuinely surprised by how easy it was to use. First, install the Modal Python client. pip install modal Next, set up Modal on your local machine.

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KDnuggets

JUNE 24, 2025

Traditional methods of understanding code structures involve reading through numerous files and documentation, which can be time-consuming and error-prone. GitDiagram offers a solution by converting GitHub repositories into interactive diagrams, providing a visual representation of the codebases architecture.

Natural Language Processing 173

Natural Language Processing Data Science Machine Learning Machine Learning 173

KDnuggets

JUNE 11, 2025

Cursor AI If you use Cursor for coding or editing, integrating multiple MCP servers has become essential for boosting its capabilities—giving you easy access to the web, databases, documentation, APIs, and external services.

Natural Language Processing 183

Natural Language Processing Data Science Machine Learning Machine Learning 183

KDnuggets

JUNE 16, 2025

PDF Data Extraction: Upload a document, highlight the fields you need, and Magical AI will transfer them into online forms or databases, saving you hours of tedious work. You can find detailed step-by-step for many different workflows in Magical AIs own documentation. It even learns your tone over time.

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Eugene Yan

JUNE 21, 2025

eugeneyan Start Here Writing Speaking Prototyping About Evaluating Long-Context Question & Answer Systems [ llm eval survey ] · 28 min read While evaluating Q&A systems is straightforward with short paragraphs, complexity increases as documents grow larger. Helpfulness: How relevant, comprehensive, and useful the response is for the user.

Clustering 268

Clustering Natural Language Processing AI AI 268

Analytics Vidhya

JULY 4, 2023

Introduction NLP (Natural Language Processing) can help us to understand huge amounts of text data. Instead of going through a huge amount of documents by hand and reading them manually, we can make use of these techniques to speed up our understanding and get to the main messages quickly.

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Natural Language Processing Analytics Analytics Python 290

Towards AI

DECEMBER 28, 2023

10+ Python packages for Natural Language Processing that you can’t miss, along with their corresponding code.Foto di Max Duzij su Unsplash Natural Language Processing is the field of Artificial Intelligence that involves text analysis. stars on GitHub. stars on GitHub.

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Natural Language Processing Python Artificial Intelligence Machine Learning 105

Data Science Dojo

SEPTEMBER 28, 2023

LlamaIndex is an orchestration framework for large language model (LLM) applications. LLMs like GPT-4 are pre-trained on massive public datasets, allowing for incredible natural language processing capabilities out of the box. The data is converted into a simple document format that is easy for LlamaIndex to process.

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Natural Language Processing Database Data Science Analytics 435

KDnuggets

OCTOBER 19, 2022

The post explains the significance of CountVectorizer and demonstrates its implementation with Python code.

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Python Natural Language Processing 271

Hacker News

AUGUST 12, 2024

In this paper we present a new method for automatic transliteration and segmentation of Unicode cuneiform glyphs using Natural Language Processing (NLP) techniques. Cuneiform is one of the earliest known writing system in the world, which documents millennia of human civilizations in the ancient Near East.

Natural Language Processing 101

Natural Language Processing Machine Learning Machine Learning Python 101

Data Science Dojo

JULY 22, 2023

In the field of software development, generative AI is already being used to automate tasks such as code generation, bug detection, and documentation. For example: Prompt: If you ask ChatGPT to “generate a function that takes a list of numbers and returns the sum of the even numbers,” it will generate the following Python code: 2.

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AWS Machine Learning Blog

DECEMBER 12, 2024

Amazon SageMaker has redesigned its Python SDK to provide a unified object-oriented interface that makes it straightforward to interact with SageMaker services. For the detailed list of pre-set values, refer to the SDK documentation. In this post, we focus on the ModelTrainer class for simplifying the training experience.

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ML ML Python AWS 103

Flipboard

DECEMBER 3, 2024

Agent architecture The following diagram illustrates the serverless agent architecture with standard authorization and real-time interaction, and an LLM agent layer using Amazon Bedrock Agents for multi-knowledge base and backend orchestration using API or Python executors. Domain-scoped agents enable code reuse across multiple agents.

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AWS AI AI Machine Learning 146

Flipboard

JUNE 26, 2025

Blog Top Posts About Topics AI Career Advice Computer Vision Data Engineering Data Science Language Models Machine Learning MLOps NLP Programming Python SQL Datasets Events Resources Cheat Sheets Recommendations Tech Briefs Advertise Join Newsletter 7 Popular LLMs Explained in 7 Minutes Get a quick overview of GPT, BERT, LLaMA, and more!

Data Science 113

Data Science Natural Language Processing Machine Learning Machine Learning 113

Data Science Dojo

MAY 22, 2023

Harrison Chase’s brainchild, LangChain, is a Python library designed to help you leverage the power of LLMs to build custom NLP applications. Document Loaders and Utils: LangChain’s Document Loaders and Utils modules simplify data access and computation. PyPDF2: Python library used to read and manipulate PDF files.

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AWS Machine Learning Blog

DECEMBER 17, 2024

This new capability from Amazon Bedrock offers a unified experience for developers of all skillsets to easily automate the extraction, transformation, and generation of relevant insights from documents, images, audio, and videos to build generative AI powered applications.

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AWS Machine Learning Blog

JANUARY 8, 2024

AWS customers in healthcare, financial services, the public sector, and other industries store billions of documents as images or PDFs in Amazon Simple Storage Service (Amazon S3). In this post, we focus on processing a large collection of documents into raw text files and storing them in Amazon S3.

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AWS Machine Learning Blog

NOVEMBER 25, 2024

John Snow Labs’ Medical Language Models is by far the most widely used natural language processing (NLP) library by practitioners in the healthcare space (Gradient Flow, The NLP Industry Survey 2022 and the Generative AI in Healthcare Survey 2024 ). To learn more, refer to the API documentation.

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AWS Machine Learning Blog

OCTOBER 24, 2023

In today’s information age, the vast volumes of data housed in countless documents present both a challenge and an opportunity for businesses. Traditional document processing methods often fall short in efficiency and accuracy, leaving room for innovation, cost-efficiency, and optimizations.

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AWS Machine Learning Blog

MAY 31, 2023

Now, Amazon Translate offers real-time document translation to seamlessly integrate and accelerate content creation and localization. This feature eliminates the wait for documents to be translated in asynchronous batch mode. This feature eliminates the wait for documents to be translated in asynchronous batch mode.

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AWS Machine Learning Blog

APRIL 7, 2025

For example, imagine a consulting firm that manages documentation for multiple healthcare providerseach customers sensitive patient records and operational documents must remain strictly separated. Using the query embedding and the metadata filter, relevant documents are retrieved from the knowledge base.

Database 125

Database AWS Natural Language Processing AI 125

Data Science Dojo

DECEMBER 6, 2023

GPT-4 with Vision combines natural language processing capabilities with computer vision. Here’s an example where GPT-4 successfully processed LATEX code to produce a Python plot. How does the GPT-4 with Vision model combine text and image inputs to provide responses?

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Towards AI

MAY 12, 2025

The Evolution of NLP Models Natural Language Processing (NLP) has transformed how machines understand and generate human language. From simple text processing to powerful language models capable of complex text generation, the journey of NLP has been remarkable. Photo by Joshua Hoehne on Unsplash 1.

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AWS Machine Learning Blog

NOVEMBER 15, 2024

This significant improvement showcases how the fine-tuning process can equip these powerful multimodal AI systems with specialized skills for excelling at understanding and answering natural language questions about complex, document-based visual information. Vision Instruct models using the SageMaker Python SDK.

ML 110

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AWS Machine Learning Blog

APRIL 19, 2023

The ability to effectively handle and process enormous amounts of documents has become essential for enterprises in the modern world. Due to the continuous influx of information that all enterprises deal with, manually classifying documents is no longer a viable option.

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AWS Machine Learning Blog

APRIL 29, 2025

The following example shows how prompt optimization converts a typical prompt for a summarization task on Anthropics Claude Haiku into a well-structured prompt for an Amazon Nova model, with sections that begin with special markdown tags such as ## Task, ### Summarization Instructions , and ### Document to Summarize.

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AWS Machine Learning Blog

NOVEMBER 6, 2024

The rise of large language models (LLMs) and foundation models (FMs) has revolutionized the field of natural language processing (NLP) and artificial intelligence (AI). For this post, we run the code in a Jupyter notebook within VS Code and use Python. We walk through a Python example in this post.

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