Search results for "NLP"

1026 documents found out of 7044 total.

• 5 Fun NLP Projects for Absolute Beginners

  Hands-on projects to help beginners understand how machines read, understand, generate, and translate human language.

  https://www.kdnuggets.com/5-fun-nlp-projects-for-absolute-beginners

• My Top Picks: 5 Free NLP Courses I’d Recommend for 2025

  Want to become an NLP pro by 2025? Check out these top free courses and learn from experts who’ve shaped the future of language models.

  https://www.kdnuggets.com/top-picks-5-free-nlp-courses-recommend-2025

• 10 GitHub Repositories to Master Natural Language Processing (NLP)

  Enhance your NLP skills through a variety of resources, including roadmaps, frameworks, courses, tutorials, example code, and projects.

  https://www.kdnuggets.com/10-github-repositories-to-master-natural-language-processing-nlp

• Cleaning and Preprocessing Text Data in Pandas for NLP Tasks

  A step-by-step guide to getting your raw text data nice and ready for Language Models and other NLP use cases!

  https://www.kdnuggets.com/cleaning-and-preprocessing-text-data-in-pandas-for-nlp-tasks

• A Tour of Python NLP Libraries

  Exploring the available text Python packages for your data workflow.

  https://www.kdnuggets.com/a-tour-of-python-nlp-libraries

• Kickstart Your NLP Journey with These 5 Free Courses

  Want to transition into the NLP field without wanting to spend a buck? You can - with these 5 courses.

  https://www.kdnuggets.com/kickstart-your-nlp-journey-with-these-5-free-courses

• KDnuggets News, October 11: 3 Data Science Projects to Land That Job • 7 Steps to Mastering NLP

  This week: What three data science projects should you choose to guarantee you get the job? • A 7 step guide to help you go from the fundamentals of machine learning and Python to Transformers, recent advances in NLP, and beyond.

  https://www.kdnuggets.com/2023/n37.html

• Job Trends in Data Analytics: NLP for Job Trend Analysis

  Perform job trend analysis and check the results using NLP.

  https://www.kdnuggets.com/job-trends-in-data-analytics-nlp-for-job-trend-analysis

• Mastering NLP Job Interviews

  What is NLP, and what types of questions related to NLP can you expect at the NLP-related job interviews?

  https://www.kdnuggets.com/2022/10/nlp-interview-questions.html

• Beyond Accuracy: Evaluating & Improving a Model with the NLP Test Library

  John Snow Labs has learned a lot about testing and delivering Responsible NLP models: not only in terms of policies and goals, but by building day-to-day tools for data scientists. The nlptest library aims to share these tools with the open-source community.

  https://www.kdnuggets.com/2023/04/john-snow-beyond-accuracy-nlp-test-library.html

• Multi-label NLP: An Analysis of Class Imbalance and Loss Function Approaches

  In this comprehensive article, we have demonstrated that a seemingly simple task of multi-label text classification can be challenging when traditional methods are applied. We have proposed the use of distribution-balancing loss functions to tackle the issue of class imbalance.

  https://www.kdnuggets.com/2023/03/multilabel-nlp-analysis-class-imbalance-loss-function-approaches.html

• Must Read NLP Papers from the Last 12 Months

  The era of large language models is here now.

  https://www.kdnuggets.com/2023/03/must-read-nlp-papers-last-12-months.html

• Simple NLP Pipelines with HuggingFace Transformers

  Transformers by HuggingFace is an all-encompassing library with state-of-the-art pre-trained models and easy-to-use tools.

  https://www.kdnuggets.com/2023/02/simple-nlp-pipelines-huggingface-transformers.html

• Top 5 NLP Cheat Sheets for Beginners to Professional

  The cheat sheets cover various NLP techniques, tasks, algorithms, frameworks, and analytics.

  https://www.kdnuggets.com/2022/12/top-5-nlp-cheat-sheets-beginners-professional.html

• Research Papers for NLP Beginners

  Read research papers on neural models, word embedding, language modeling, and attention & transformers.

  https://www.kdnuggets.com/2022/11/research-papers-nlp-beginners.html

• 5 Linguistics Courses for NLP Practitioners

  This collection of 5 courses is intended to help NLP practitioners or hopefuls acquire some of their lacking linguistics knowledge.

  https://www.kdnuggets.com/2022/11/5-linguistics-courses-nlp-practitioners.html

• The Ultimate Guide To Different Word Embedding Techniques In NLP

  A machine can only understand numbers. As a result, converting text to numbers, called embedding text, is an actively researched topic. In this article, we review different word embedding techniques for converting text into vectors.

  https://www.kdnuggets.com/2021/11/guide-word-embedding-techniques-nlp.html

• Getting Started with spaCy for NLP

  In this blog, we will explore how to get started with spaCy right from the installation to explore the various functionalities it provides.

  https://www.kdnuggets.com/2022/11/getting-started-spacy-nlp.html

• The ABCs of NLP, From A to Z

  There is no shortage of tools today that can help you through the steps of natural language processing, but if you want to get a handle on the basics this is a good place to start. Read about the ABCs of NLP, all the way from A to Z.

  https://www.kdnuggets.com/2022/10/abcs-nlp-a-to-z.html

• KDnuggets News, October 12: 10 Cheat Sheets You Need To Ace Data Science Interview • NLP Interview Questions

  10 Cheat Sheets You Need To Ace Data Science Interview • NLP Interview Questions • A Day in the Life of a Machine Learning Engineer • 11 Questions About Data Engineers: What's the profession about, and where's it heading? • The ABCs of NLP, From A to Z

  https://www.kdnuggets.com/2022/n40.html

• 8 Innovative BERT Knowledge Distillation Papers That Have Changed The Landscape of NLP

  All of the papers present a particular point of view of findings in the BERT utilization.

  https://www.kdnuggets.com/2022/09/eight-innovative-bert-knowledge-distillation-papers-changed-nlp-landscape.html

• NLP, NLU, and NLG: What’s The Difference? A Comprehensive Guide

  This article aims to quickly cover the similarities and differences between NLP, NLU, and NLG and talk about what the future for NLP holds.

  https://www.kdnuggets.com/2022/06/nlp-nlu-nlg-difference-comprehensive-guide.html

• oBERT: Compound Sparsification Delivers Faster Accurate Models for NLP

  Discover "compound sparsification" and how to apply it to BERT models for 10x compression and GPU-level latency on commodity CPUs.

  https://www.kdnuggets.com/2022/05/obert-compound-sparsification-delivers-faster-accurate-models-nlp.html

• Machine Learning’s Sweet Spot: Pure Approaches in NLP and Document Analysis

  While it is true that Machine Learning today isn’t ready for prime time in many business cases that revolve around Document Analysis, there are indeed scenarios where a pure ML approach can be considered.

  https://www.kdnuggets.com/2022/05/machine-learning-sweet-spot-pure-approaches-nlp-document-analysis.html

• The Range of NLP Applications in the Real World: A Different Solution To Each Problem

  Most companies look at it like it’s one big technology, and assume the vendors’ offerings might differ in product quality and price but ultimately be largely the same. Truth is, NLP is not one thing; it’s not one tool, but rather a toolbox.

  https://www.kdnuggets.com/2022/03/different-solution-problem-range-nlp-applications-real-world.html

• Explain NLP Models with LIME

  It is important to know how LIME reaches to its final outputs for explaining a prediction done for text data. In this article, I have shared that concept by enlightening the components of LIME.

  https://www.kdnuggets.com/2022/01/explain-nlp-models-lime.html

• Where NLP is heading">Where NLP is heading

  Natural language processing research and applications are moving forward rapidly. Several trends have emerged on this progress, and point to a future of more exciting possibilities and interesting opportunities in the field.

  https://www.kdnuggets.com/2021/11/where-nlp-is-heading.html

• 7 Top Open Source Datasets to Train Natural Language Processing (NLP) & Text Models

  With a lot of excitement and research around NLP, there are growing opportunities to apply these technologies to real-world scenarios. It's not trivial to become familiar with NLP and these open-source data sets can help you increase your skills.

  https://www.kdnuggets.com/2021/11/top-open-source-datasets-nlp.html

• The Evolution of Tokenization – Byte Pair Encoding in NLP

  Though we have SOTA algorithms for tokenization, it's always a good practice to understand the evolution trail and learning how have we reached here. Read this introduction to Byte Pair Encoding.

  https://www.kdnuggets.com/2021/10/evolution-tokenization-byte-pair-encoding-nlp.html

• NLP Insights for the Penguin Café Orchestra

  We give an example of how to use Expert.ai and Python to investigate favorite music albums.

  https://www.kdnuggets.com/2021/08/expert-nlp-insights-music.html

• The Best SOTA NLP Course is Free!

  Hugging Face has recently released a course on using its libraries and ecosystem for practical NLP, and it appears to be very comprehensive. Have a look for yourself.

  https://www.kdnuggets.com/2021/07/best-sota-nlp-course-free.html

• Overview of AutoNLP from Hugging Face with Example Project

  AutoNLP is a beta project from Hugging Face that builds on the company’s work with its Transformer project. With AutoNLP you can get a working model with just a few simple terminal commands.

  https://www.kdnuggets.com/2021/06/overview-autonlp-hugging-face-example-project.html

• The Best Way to Learn Practical NLP?

  Hugging Face has just released a course on using its libraries and ecosystem for practical NLP, and it appears to be very comprehensive. Have a look for yourself.

  https://www.kdnuggets.com/2021/06/best-way-learn-practical-nlp.html

• A Graph-based Text Similarity Method with Named Entity Information in NLP

  In this article, the author summarizes the 2017 paper "A Graph-based Text Similarity Measure That Employs Named Entity Information" as per their understanding. Better understand the concepts by reading along.

  https://www.kdnuggets.com/2021/06/graph-based-text-similarity-method-named-entity-information-nlp.html

• 4 Tips for Dataset Curation for NLP Projects

  You have heard it before, and you will hear it again. It's all about the data. Curating the right data is also so important than just curating any data. When dealing with text data, many hard-earned lessons have been learned by others over the years, and here are four data curation tips that you should be sure to follow during your next NLP project.

  https://www.kdnuggets.com/2021/05/4-tips-dataset-curation-nlp-projects.html

• Similarity Metrics in NLP

  This post covers the use of euclidean distance, dot product, and cosine similarity as NLP similarity metrics.

  https://www.kdnuggets.com/2021/05/similarity-metrics-nlp.html

• Introducing The NLP Index

  The NLP Index is a brand new resource for NLP code discovery, combining and indexing more than 3,000 paper and code pairs at launch. If you are interested in NLP research and locating the code and papers needed to understand an implement the latest research, you should check it out.

  https://www.kdnuggets.com/2021/04/nlp-index.html

• Production-Ready Machine Learning NLP API with FastAPI and spaCy

  Learn how to implement an API based on FastAPI and spaCy for Named Entity Recognition (NER), and see why the author used FastAPI to quickly build a fast and robust machine learning API.

  https://www.kdnuggets.com/2021/04/production-ready-machine-learning-nlp-api-fastapi-spacy.html

• How to Begin Your NLP Journey

  In this blog post, learn how to process text using Python.

  https://www.kdnuggets.com/2021/03/begin-nlp-journey.html

• Reducing the High Cost of Training NLP Models With SRU++

  The increasing computation time and costs of training natural language models (NLP) highlight the importance of inventing computationally efficient models that retain top modeling power with reduced or accelerated computation. A single experiment training a top-performing language model on the 'Billion Word' benchmark would take 384 GPU days and as much as $36,000 using AWS on-demand instances.

  https://www.kdnuggets.com/2021/03/reducing-high-cost-training-nlp-models-sru.html

• Using NLP to improve your Resume

  This article discusses performing keyword matching and text analysis on job descriptions.

  https://www.kdnuggets.com/2021/02/nlp-improve-resume.html

• 6 NLP Techniques Every Data Scientist Should Know">6 NLP Techniques Every Data Scientist Should Know

  Natural language processing has already begun to transform to way humans interact with computers, and its advances are moving rapidly. The field is built on core methods that must first be understood, with which you can then launch your data science projects to a new level of sophistication and value.

  https://www.kdnuggets.com/2021/02/6-nlp-techniques.html

• Vision Transformers: Natural Language Processing (NLP) Increases Efficiency and Model Generality

  Why do we hear so little about transformer models applied to computer vision tasks? What about attention in computer vision networks?

  https://www.kdnuggets.com/2021/02/vision-transformers-nlp-efficiency-model-generality.html

• Topic: NLP

  Here are the most recent and most popular posts on NLP

  https://www.kdnuggets.com/topic/nlp

• Roadmap to Natural Language Processing (NLP)">Roadmap to Natural Language Processing (NLP)

  Check out this introduction to some of the most common techniques and models used in Natural Language Processing (NLP).

  https://www.kdnuggets.com/2020/10/roadmap-natural-language-processing-nlp.html

• An Introduction to NLP and 5 Tips for Raising Your Game

  This article is a collection of things the author would like to have known when they started out in NLP. Perhaps it will be useful for you.

  https://www.kdnuggets.com/2020/09/introduction-nlp-5-tips-raising-your-game.html

• The NLP Model Forge: Generate Model Code On Demand">The NLP Model Forge: Generate Model Code On Demand

  You've seen their Big Bad NLP Database and The Super Duper NLP Repo. Now Quantum Stat is back with its most ambitious NLP product yet: The NLP Model Forge.

  https://www.kdnuggets.com/2020/08/nlp-model-forge.html

• Must-read NLP and Deep Learning articles for Data Scientists">Must-read NLP and Deep Learning articles for Data Scientists

  NLP and deep learning continue to advance, nearly on a daily basis. Check out these recent must-read guides, feature articles, and other resources to keep you on top of the latest advancements and ahead of the curve.

  https://www.kdnuggets.com/2020/08/must-read-nlp-deep-learning-articles.html

• The Unreasonable Progress of Deep Neural Networks in Natural Language Processing (NLP)

  Natural language processing has made incredible advances through advanced techniques in deep learning. Learn about these powerful models, and find how close (or far away) these approaches are to human-level understanding.

  https://www.kdnuggets.com/2020/06/unreasonable-progress-deep-neural-networks-nlp.html

• Top May Stories: The Best NLP with Deep Learning Course is Free

  Also: How to Think Like a Data Scientist; Python For Everybody: The Free eBook; Automated Machine Learning: The Free eBook.

  https://www.kdnuggets.com/2020/06/top-stories-2020-may.html

• GPT-3, a giant step for Deep Learning and NLP?

  Recently, OpenAI announced a new successor to their language model, GPT-3, that is now the largest model trained so far with 175 billion parameters. Training a language model this large has its merits and limitations, so this article covers some of its most interesting and important aspects.

  https://www.kdnuggets.com/2020/06/gpt-3-deep-learning-nlp.html

• From Languages to Information: Another Great NLP Course from Stanford">From Languages to Information: Another Great NLP Course from Stanford

  Check out another example of a Stanford NLP course and its freely available courseware.

  https://www.kdnuggets.com/2020/06/languages-information-another-great-nlp-course-stanford.html

• Four Ways to Apply NLP in Financial Services

  Natural language processing (NLP) is increasingly used to review unstructured content or spot trends in markets. How is Refinitiv Labs applying NLP in financial services to meet challenges around investment decision-making and risk management?

  https://www.kdnuggets.com/2020/06/four-ways-apply-nlp-financial-services.html

• Top Stories, May 18-24: The Best NLP with Deep Learning Course is Free

  Also: Automated Machine Learning: The Free eBook; Sparse Matrix Representation in Python; Build and deploy your first machine learning web app; Complex logic at breakneck speed: Try Julia for data science

  https://www.kdnuggets.com/2020/05/top-news-week-0518-0524.html

• The Best NLP with Deep Learning Course is Free">The Best NLP with Deep Learning Course is Free

  Stanford's Natural Language Processing with Deep Learning is one of the most respected courses on the topic that you will find anywhere, and the course materials are freely available online.

  https://www.kdnuggets.com/2020/05/best-nlp-deep-learning-course-free.html

• Spotting Controversy with NLP

  In this article, I’ll introduce you to a hot-topic in financial services and describe how a leading data provider is using data science and NLP to streamline how they find insights in unstructured data.

  https://www.kdnuggets.com/2020/05/spotting-controversy-nlp.html

• The Super Duper NLP Repo: 100 Ready-to-Run Colab Notebooks">The Super Duper NLP Repo: 100 Ready-to-Run Colab Notebooks

  Check out this repository of more than 100 freely-accessible NLP notebooks, curated from around the internet, and ready to launch in Colab with a single click.

  https://www.kdnuggets.com/2020/04/super-duper-nlp-repo.html

• The Big Bad NLP Database: Access Nearly 300 Datasets">The Big Bad NLP Database: Access Nearly 300 Datasets

  Check out this database of nearly 300 freely-accessible NLP datasets, curated from around the internet.

  https://www.kdnuggets.com/2020/02/big-bad-nlp-database.html

• NLP Year in Review — 2019

  In this blog post, I want to highlight some of the most important stories related to machine learning and NLP that I came across in 2019.

  https://www.kdnuggets.com/2020/01/nlp-year-review-2019.html

• An Introductory Guide to NLP for Data Scientists with 7 Common Techniques">An Introductory Guide to NLP for Data Scientists with 7 Common Techniques

  Data Scientists work with tons of data, and many times that data includes natural language text. This guide reviews 7 common techniques with code examples to introduce you the essentials of NLP, so you can begin performing analysis and building models from textual data.

  https://www.kdnuggets.com/2020/01/intro-guide-nlp-data-scientists.html

• Lit BERT: NLP Transfer Learning In 3 Steps

  PyTorch Lightning is a lightweight framework which allows anyone using PyTorch to scale deep learning code easily while making it reproducible. In this tutorial we’ll use Huggingface's implementation of BERT to do a finetuning task in Lightning.

  https://www.kdnuggets.com/2019/11/lit-bert-nlp-transfer-learning-3-steps.html

• Spark NLP 101: LightPipeline

  A Pipeline is specified as a sequence of stages, and each stage is either a Transformer or an Estimator. These stages are run in order, and the input DataFrame is transformed as it passes through each stage. Now let’s see how this can be done in Spark NLP using Annotators and Transformers.

  https://www.kdnuggets.com/2019/11/spark-nlp-101-lightpipeline.html

• Content-based Recommender Using Natural Language Processing (NLP)

  A guide to build a content-based movie recommender model based on NLP.

  https://www.kdnuggets.com/2019/11/content-based-recommender-using-natural-language-processing-nlp.html

• Understanding NLP and Topic Modeling Part 1

  In this post, we seek to understand why topic modeling is important and how it helps us as data scientists.

  https://www.kdnuggets.com/2019/11/understanding-nlp-topic-modeling-part-1.html

• How to Create a Vocabulary for NLP Tasks in Python

  This post will walkthrough a Python implementation of a vocabulary class for storing processed text data and related metadata in a manner useful for subsequently performing NLP tasks.

  https://www.kdnuggets.com/2019/11/create-vocabulary-nlp-tasks-python.html

• Introduction to Natural Language Processing (NLP)

  Have you ever wondered how your personal assistant (e.g: Siri) is built? Do you want to build your own? Perfect! Let’s talk about Natural Language Processing.

  https://www.kdnuggets.com/2019/10/introduction-natural-language-processing.html

• Multi-Task Learning – ERNIE 2.0: State-of-the-Art NLP Architecture Intuitively Explained

  The tech giant Baidu unveiled its state-of-the-art NLP architecture ERNIE 2.0 earlier this year, which scored significantly higher than XLNet and BERT on all tasks in the GLUE benchmark. This major breakthrough in NLP takes advantage of a new innovation called “Continual Incremental Multi-Task Learning”.

  https://www.kdnuggets.com/2019/10/multi-task-learning-ernie-sota-nlp-architecture.html

• TensorFlow vs PyTorch vs Keras for NLP">TensorFlow vs PyTorch vs Keras for NLP

  These three deep learning frameworks are your go-to tools for NLP, so which is the best? Check out this comparative analysis based on the needs of NLP, and find out where things are headed in the future.

  https://www.kdnuggets.com/2019/09/tensorflow-pytorch-keras-nlp.html

• Deep Learning for NLP: Creating a Chatbot with Keras!">Deep Learning for NLP: Creating a Chatbot with Keras!

  Learn how to use Keras to build a Recurrent Neural Network and create a Chatbot! Who doesn’t like a friendly-robotic personal assistant?

  https://www.kdnuggets.com/2019/08/deep-learning-nlp-creating-chatbot-keras.html

• Top KDnuggets tweets, Aug 07-13: Deep Learning Cheat Sheets; 12 NLP Researchers, Practitioners To Follow

  Deep Learning Cheat Sheets; 12 NLP Researchers, Practitioners & Innovators You Should Be Following; Knowing Your Neighbours: Machine Learning on Graphs.

  https://www.kdnuggets.com/2019/08/top-tweets-aug07-13.html

• 12 NLP Researchers, Practitioners & Innovators You Should Be Following">12 NLP Researchers, Practitioners & Innovators You Should Be Following

  Check out this list of NLP researchers, practitioners and innovators you should be following, including academics, practitioners, developers, entrepreneurs, and more.

  https://www.kdnuggets.com/2019/08/nlp-researchers-practitioners-innovators-should-follow.html

• Deep Learning for NLP: ANNs, RNNs and LSTMs explained!">Deep Learning for NLP: ANNs, RNNs and LSTMs explained!

  Learn about Artificial Neural Networks, Deep Learning, Recurrent Neural Networks and LSTMs like never before and use NLP to build a Chatbot!

  https://www.kdnuggets.com/2019/08/deep-learning-nlp-explained.html

• Adapters: A Compact and Extensible Transfer Learning Method for NLP

  Adapters obtain comparable results to BERT on several NLP tasks while achieving parameter efficiency.

  https://www.kdnuggets.com/2019/07/adapters-compact-extensible-transfer-learning-method-nlp.html

• A Gentle Guide to Starting Your NLP Project with AllenNLP

  For those who aren’t familiar with AllenNLP, I will give a brief overview of the library and let you know the advantages of integrating it to your project.

  https://www.kdnuggets.com/2019/07/gentle-guide-starting-nlp-project-allennlp.html

• NLP vs. NLU: from Understanding a Language to Its Processing">NLP vs. NLU: from Understanding a Language to Its Processing

  As AI progresses and the technology becomes more sophisticated, we expect existing techniques to evolve. With these changes, will the well-founded natural language processing give way to natural language understanding? Or, are the two concepts subtly distinct to hold their own niche in AI?

  https://www.kdnuggets.com/2019/07/nlp-vs-nlu-understanding-language-processing.html

• XLNet Outperforms BERT on Several NLP Tasks">XLNet Outperforms BERT on Several NLP Tasks

  XLNet is a new pretraining method for NLP that achieves state-of-the-art results on several NLP tasks.

  https://www.kdnuggets.com/2019/07/xlnet-outperforms-bert-several-nlp-tasks.html

• Spark NLP: Getting Started With The World’s Most Widely Used NLP Library In The Enterprise"> Spark NLP: Getting Started With The World’s Most Widely Used NLP Library In The Enterprise

  The Spark NLP library has become a popular AI framework that delivers speed and scalability to your projects. Check out what's under the hood and learn about how to getting started leveraging Spark NLP from John Snow Labs.

  https://www.kdnuggets.com/2019/06/spark-nlp-getting-started-with-worlds-most-widely-used-nlp-library-enterprise.html

• NLP and Computer Vision Integrated">NLP and Computer Vision Integrated

  Computer vision and NLP developed as separate fields, and researchers are now combining these tasks to solve long-standing problems across multiple disciplines.

  https://www.kdnuggets.com/2019/06/nlp-computer-vision-integrated.html

• Analyzing Tweets with NLP in Minutes with Spark, Optimus and Twint

  Social media has been gold for studying the way people communicate and behave, in this article I’ll show you the easiest way of analyzing tweets without the Twitter API and scalable for Big Data.

  https://www.kdnuggets.com/2019/05/analyzing-tweets-nlp-spark-optimus-twint.html

• Your Guide to Natural Language Processing (NLP)

  This extensive post covers NLP use cases, basic examples, Tokenization, Stop Words Removal, Stemming, Lemmatization, Topic Modeling, the future of NLP, and more.

  https://www.kdnuggets.com/2019/05/guide-natural-language-processing-nlp.html

• A Complete Exploratory Data Analysis and Visualization for Text Data: Combine Visualization and NLP to Generate Insights

  Visually representing the content of a text document is one of the most important tasks in the field of text mining as a Data Scientist or NLP specialist. However, there are some gaps between visualizing unstructured (text) data and structured data.

  https://www.kdnuggets.com/2019/05/complete-exploratory-data-analysis-visualization-text-data.html

• All you need to know about text preprocessing for NLP and Machine Learning

  We present a comprehensive introduction to text preprocessing, covering the different techniques including stemming, lemmatization, noise removal, normalization, with examples and explanations into when you should use each of them.

  https://www.kdnuggets.com/2019/04/text-preprocessing-nlp-machine-learning.html

• Getting started with NLP using the PyTorch framework

  We discuss the classes that PyTorch provides for helping with Natural Language Processing (NLP) and how they can be used for related tasks using recurrent layers.

  https://www.kdnuggets.com/2019/04/nlp-pytorch.html

• Building NLP Classifiers Cheaply With Transfer Learning and Weak Supervision

  In this blog, I’ll walk you through a personal project in which I cheaply built a classifier to detect anti-semitic tweets, with no public dataset available, by combining weak supervision and transfer learning.

  https://www.kdnuggets.com/2019/03/building-nlp-classifiers-cheaply-transfer-learning-weak-supervision.html

• Word Embeddings in NLP and its Applications

  Word embeddings such as Word2Vec is a key AI method that bridges the human understanding of language to that of a machine and is essential to solving many NLP problems. Here we discuss applications of Word2Vec to Survey responses, comment analysis, recommendation engines, and more.

  https://www.kdnuggets.com/2019/02/word-embeddings-nlp-applications.html

• How I used NLP (Spacy) to screen Data Science Resumes

  A real life example of when using NLP can help filter down a list of candidates for a job opening, with full source code and methodology.

  https://www.kdnuggets.com/2019/02/nlp-spacy-data-science-resumes.html

• 10 Exciting Ideas of 2018 in NLP

  We outline a selection of exciting developments in NLP from the last year, and include useful recent papers and images to help further assist with your learning.

  https://www.kdnuggets.com/2019/01/10-exciting-ideas-2018-nlp.html

• How to solve 90% of NLP problems: a step-by-step guide">How to solve 90% of NLP problems: a step-by-step guide

  Read this insightful, step-by-step article on how to use machine learning to understand and leverage text.

  https://www.kdnuggets.com/2019/01/solve-90-nlp-problems-step-by-step-guide.html

• Top 10 Books on NLP and Text Analysis">Top 10 Books on NLP and Text Analysis

  When it comes to choosing the right book, you become immediately overwhelmed with the abundance of possibilities. In this review, we have collected our Top 10 NLP and Text Analysis Books of all time, ranging from beginners to experts.

  https://www.kdnuggets.com/2019/01/top-10-books-nlp-text-analysis.html

• NLP Overview: Modern Deep Learning Techniques Applied to Natural Language Processing">NLP Overview: Modern Deep Learning Techniques Applied to Natural Language Processing

  Trying to keep up with advancements at the overlap of neural networks and natural language processing can be troublesome. That's where the today's spotlighted resource comes in.

  https://www.kdnuggets.com/2019/01/nlp-overview-modern-deep-learning-techniques.html

• BERT: State of the Art NLP Model, Explained

  BERT’s key technical innovation is applying the bidirectional training of Transformer, a popular attention model, to language modelling. It has caused a stir in the Machine Learning community by presenting state-of-the-art results in a wide variety of NLP tasks.

  https://www.kdnuggets.com/2018/12/bert-sota-nlp-model-explained.html

• More Effective Transfer Learning for NLP

  Until recently, the natural language processing community was lacking its ImageNet equivalent — a standardized dataset and training objective to use for training base models.

  https://www.kdnuggets.com/2018/10/more-effective-transfer-learning-nlp.html

• Deep Learning for NLP: An Overview of Recent Trends">Deep Learning for NLP: An Overview of Recent Trends

  A new paper discusses some of the recent trends in deep learning based natural language processing (NLP) systems and applications. The focus is on the review and comparison of models and methods that have achieved state-of-the-art (SOTA) results on various NLP tasks and some of the current best practices for applying deep learning in NLP.

  https://www.kdnuggets.com/2018/09/deep-learning-nlp-overview-recent-trends.html

• Emotion and Sentiment Analysis: A Practitioner’s Guide to NLP

  Sentiment analysis is widely used, especially as a part of social media analysis for any domain, be it a business, a recent movie, or a product launch, to understand its reception by the people and what they think of it based on their opinions or, you guessed it, sentiment!

  https://www.kdnuggets.com/2018/08/emotion-sentiment-analysis-practitioners-guide-nlp-5.html

• Named Entity Recognition: A Practitioner’s Guide to NLP

  Named entity recognition (NER) , also known as entity chunking/extraction , is a popular technique used in information extraction to identify and segment the named entities and classify or categorize them under various predefined classes.

  https://www.kdnuggets.com/2018/08/named-entity-recognition-practitioners-guide-nlp-4.html

• Understanding Language Syntax and Structure: A Practitioner’s Guide to NLP">Understanding Language Syntax and Structure: A Practitioner’s Guide to NLP

  Knowledge about the structure and syntax of language is helpful in many areas like text processing, annotation, and parsing for further operations such as text classification or summarization.

  https://www.kdnuggets.com/2018/08/understanding-language-syntax-and-structure-practitioners-guide-nlp-3.html

• Text Wrangling & Pre-processing: A Practitioner’s Guide to NLP

  I will highlight some of the most important steps which are used heavily in Natural Language Processing (NLP) pipelines and I frequently use them in my NLP projects.

  https://www.kdnuggets.com/2018/08/practitioners-guide-processing-understanding-text-2.html

• Data Retrieval with Web Scraping: A Practitioner’s Guide to NLP

  Proven and tested hands-on strategies to tackle NLP tasks.

  https://www.kdnuggets.com/2018/07/practitioners-guide-processing-understanding-text-1.html

• Comparison of Top 6 Python NLP Libraries">Comparison of Top 6 Python NLP Libraries

  Today, we want to outline and compare the most popular and helpful natural language processing libraries, based on our experience.

  https://www.kdnuggets.com/2018/07/comparison-top-6-python-nlp-libraries.html

• 30 Free Resources for Machine Learning, Deep Learning, NLP & AI">30 Free Resources for Machine Learning, Deep Learning, NLP & AI

  Check out this collection of 30 ML, DL, NLP & AI resources for beginners, starting from zero and slowly progressing to the point that readers should have an idea of where to go next.

  https://www.kdnuggets.com/2018/06/30-free-resources-machine-learning-deep-learning-nlp-ai.html

• Natural Language Processing Nuggets: Getting Started with NLP

  Check out this collection of NLP resources for beginners, starting from zero and slowly progressing to the point that readers should have an idea of where to go next.

  https://www.kdnuggets.com/2018/06/getting-started-natural-language-processing.html

• Why Deep Learning is perfect for NLP (Natural Language Processing)">Why Deep Learning is perfect for NLP (Natural Language Processing)

  Deep learning brings multiple benefits in learning multiple levels of representation of natural language. Here we will cover the motivation of using deep learning and distributed representation for NLP, word embeddings and several methods to perform word embeddings, and applications.

  https://www.kdnuggets.com/2018/04/why-deep-learning-perfect-nlp-natural-language-processing.html

• An NLP Approach to Analyzing Twitter, Trump, and Profanity

  Who swears more? Do Twitter users who mention Donald Trump swear more than those who mention Hillary Clinton? Let’s find out by taking a natural language processing approach (or, NLP for short) to analyzing tweets.

  https://www.kdnuggets.com/2016/11/nlp-approach-analyzing-twitter-trump-profanity.html

• Attention and Memory in Deep Learning and NLP

  An overview of attention mechanisms and memory in deep neural networks and why they work, including some specific applications in natural language processing and beyond.

  https://www.kdnuggets.com/2016/01/attention-memory-deep-learning-nlp.html

• Understanding Convolutional Neural Networks for NLP

  Dive into the world of Convolution Neural Networks (CNN), learn how they work, how to apply them for NLP, and how to tune CNN hyperparameters for best performance.

  https://www.kdnuggets.com/2015/11/understanding-convolutional-neural-networks-nlp.html

• TweetNLP: Twitter Natural Language Processing

  A short overview of Natural Language Processing tools and utilities developed by Prof. Noah Smith, CMU and his team to analyze Twitter data.

  https://www.kdnuggets.com/2014/10/tweetnlp-twitter-natural-language-processing.html

• 10 Most Popular GitHub Repositories for Learning AI

  The most popular GitHub repositories to help you learn AI, from fundamentals and math to LLMs, agents, computer vision, and real-world production systems.

  https://www.kdnuggets.com/10-most-popular-github-repositories-for-learning-ai

• 10 GitHub Repositories to Master Machine Learning Deployment

  Master the essential skill of deploying machine learning models with courses, projects, examples, resources, and interview questions.

  https://www.kdnuggets.com/10-github-repositories-to-master-machine-learning-deployment

• Top 5 Open-Source LLM Evaluation Platforms

  If you’re building an LLM app, these open-source tools help you test, track, and improve your model’s performance easily.

  https://www.kdnuggets.com/top-5-open-source-llm-evaluation-platforms

• My Honest Review on Abacus AI: ChatLLM, DeepAgent & Enterprise

  Abacus AI offers the world’s first professional and enterprise AI Super Assistant. It’s an all-in-one AI platform for the top language, image, voic,e and video models along with all the tooling and infrastructure to support them. Abacus can connect to all YOUR data and apply AI to automate work.

  https://www.kdnuggets.com/2025/11/abacus/my-honest-take-on-abacus-ai-chatllm-deepagent-enterprise

• The 5 FREE Must-Read Books for Every AI Engineer

  A handpicked list of free reads that teach you the science, logic, and real-world side of artificial intelligence.

  https://www.kdnuggets.com/the-5-free-must-read-books-for-every-ai-engineer

• The 5 FREE Must-Read Books for Every LLM Engineer

  Discover 5 free must-read books that cover theory, systems, linguistics, interpretability, and security side of large language models.

  https://www.kdnuggets.com/the-5-free-must-read-books-for-every-llm-engineer

• What’s on My Bookmarks Bar: Data Science Edition

  Save time by keeping top resources and tools at your fingertips.

  https://www.kdnuggets.com/whats-on-my-bookmarks-bar-data-science-edition

• 7 LinkedIn Tricks to Get Noticed by Recruiters

  No recruiters contacted you recently? Here are 7 LinkedIn tricks to make you stand out.

  https://www.kdnuggets.com/7-linkedin-tricks-to-get-noticed-by-recruiters

• The Algorithmic X-Men

  We've assembled our team of Algorithmic X-Men, seven heroes mapped to seven dependable workhorses of machine learning.

  https://www.kdnuggets.com/the-algorithmic-x-men

• 5 Cutting-Edge Natural Language Processing Trends Shaping 2026

  In this article, we discuss five cutting-edge NLP trends that will shape 2026.

  https://www.kdnuggets.com/5-cutting-edge-natural-language-processing-trends-shaping-2026

• 10 Python One-Liners to Optimize Your Hugging Face Transformers Pipelines

  In this article, we present 10 powerful Python one-liners that will help you optimize your Hugging Face pipeline() workflows.

  https://www.kdnuggets.com/10-python-one-liners-to-optimize-your-hugging-face-transformers-pipelines

• 5 Free AI Courses from Hugging Face

  Hands-on, community driven courses on LLMs, AI agents, MCPs, diffusion models, and reinforcement learning.

  https://www.kdnuggets.com/5-free-ai-courses-from-hugging-face

• How to Become a Machine Learning Engineer

  Discover the steps you need to kickstart your journey as a machine learning engineer in today’s AI-driven world.

  https://www.kdnuggets.com/how-to-become-a-machine-learning-engineer-2

• 7 Beginner Machine Learning Projects To Complete This Weekend

  In this article, we will explore seven simple machine learning projects that will help you learn important skills and improve your career.

  https://www.kdnuggets.com/7-beginner-machine-learning-projects-complete-this-weekend

• Shortcuts for the Long Run: Automated Workflows for Aspiring Data Engineers

  Tired of repeating the same data tasks? Automate them. This article shows beginners how to build efficient, low-maintenance data engineering workflows that pay off in the long run.

  https://www.kdnuggets.com/shortcuts-for-the-long-run-automated-workflows-for-aspiring-data-engineers

• When Do I Need to Use an LLM?

  This article aims to bring the conversation about LLMs back down to earth, exploring not only the wide array of use cases where LLMs can add real value, but also the limitations they face.

  https://www.kdnuggets.com/when-do-i-need-to-use-an-llm

• 10 GitHub Repositories for Machine Learning Projects

  Explore these top machine learning repositories to build your skills, portfolio, and creativity through hands-on projects, real-world challenges, and AI resources.

  https://www.kdnuggets.com/10-github-repositories-for-machine-learning-projects

• Bootstrapping Your Freelance Data Science Business for Cheap

  This article provides a clear, practical guide to help you choose a niche, find clients, and scale your business effectively.

  https://www.kdnuggets.com/bootstrapping-your-freelance-data-science-business-with-minimal-tools

• 5 Ways to Transition Into AI from a Non-Tech Background

  You have a non-tech background? Sure, you can transition into AI. Here are five practical ways of doing it.

  https://www.kdnuggets.com/5-ways-to-transition-into-ai-from-a-non-tech-background

• Large Language Models: A Self-Study Roadmap

  A complete beginner’s roadmap to understanding and building with large language models explained simply and with hands-on resources.

  https://www.kdnuggets.com/large-language-models-a-self-study-roadmap

• NotebookLM + Deep Research: The Ultimate Learning Hack

  Let’s unlock smarter, faster learning by combining NotebookLM with deep research strategies.

  https://www.kdnuggets.com/notebooklm-deep-research-the-ultimate-learning-hack

• Building a Custom PDF Parser with PyPDF and LangChain

  PDFs look simple — until you try to parse one. Here’s how to build your own parser.

  https://www.kdnuggets.com/building-a-custom-pdf-parser-with-pypdf-and-langchain

• 10 Generative AI Key Concepts Explained

  In this article we explore 10 generative AI concepts that are key to understanding, whether you are an engineer, user, or consumer of generative AI.

  https://www.kdnuggets.com/10-generative-ai-key-concepts-explained

• From Python to AI Engineer: A Self-Study Roadmap

  A practical roadmap for Python programmers to develop the advanced skills, specialized knowledge, and engineering mindset needed to become successful AI engineers in 2025.

  https://www.kdnuggets.com/from-python-to-ai-engineer-a-self-study-roadmap