AWS Machine Learning Blog

AUGUST 21, 2023

Explainability of machine learning (ML) models used in the medical domain is becoming increasingly important because models need to be explained from a number of perspectives in order to gain adoption. Explainability of these predictions is required in order for clinicians to make the correct choices on a patient-by-patient basis.

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IBM Journey to AI blog

MARCH 27, 2024

In recent years, remarkable strides have been achieved in crafting extensive foundation language models for natural language processing (NLP). As previously explained, spend data is more readily available in an organization and is a common proxy of quantity of goods/services.

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AWS Machine Learning Blog

JANUARY 25, 2023

Model explainability refers to the process of relating the prediction of a machine learning (ML) model to the input feature values of an instance in humanly understandable terms. This field is often referred to as explainable artificial intelligence (XAI). In this post, we illustrate the use of Clarify for explaining NLP models.

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AI Weekly

APRIL 11, 2024

Read the blog] global.ntt In The News When an antibiotic fails: MIT scientists are using AI to target “sleeper” bacteria mit.edu Microsoft AI opens London hub to access ‘enormous pool’ of talent Microsoft is doubling down on its AI efforts in the UK with the opening of a major new AI hub in London. No legacy process is safe.

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Chatbots Life

SEPTEMBER 11, 2023

It provides a detailed overview of each library’s unique contributions and explains how they can be combined to create a functional system that can detect and correct linguistic errors in text data. This limitation has paved the way for more advanced solutions that harness the power of Natural Language Processing (NLP).

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Heartbeat

JUNE 22, 2023

Natural language processing (NLP) can help with this. In this post, we’ll look at how natural language processing (NLP) may be utilized to create smart chatbots that can comprehend and reply to natural language requests. What is NLP? Sentiment analysis, language translation, and speech recognition are a few NLP applications.

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Heartbeat

MARCH 15, 2023

But now, a computer can be taught to comprehend and process human language through Natural Language Processing (NLP), which was implemented, to make computers capable of understanding spoken and written language. This article will explain to you in detail about RoBERTa and if you do not know about BERT please click on the associated link.

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Heartbeat

FEBRUARY 7, 2023

image by rawpixel.com Understanding the concept of language models in natural language processing (NLP) is very important to anyone working in the Deep learning and machine learning space. They are essential to a variety of NLP activities, including speech recognition, machine translation, and text summarization.

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Heartbeat

JUNE 6, 2023

In recent years, researchers have also explored using GCNs for natural language processing (NLP) tasks, such as text classification , sentiment analysis , and entity recognition. This article provides a brief overview of GCNs for NLP tasks and how to implement them using PyTorch and Comet.

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Heartbeat

JULY 5, 2023

It interprets user input and generates suitable responses using artificial intelligence (AI) and natural language processing (NLP). It necessitates a thorough knowledge of natural language processing (NLP) methods. In this article, you will learn how to use RL and NLP to create an entire chatbot system. Why is NLP Required?

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IBM Journey to AI blog

JUNE 26, 2023

Possibilities are growing that include assisting in writing articles, essays or emails; accessing summarized research; generating and brainstorming ideas; dynamic search with personalized recommendations for retail and travel; and explaining complicated topics for education and training. What is generative AI? What is watsonx.governance?

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IBM Journey to AI blog

JANUARY 25, 2024

Additionally, the models themselves are created from limited architectures: “Almost all state-of-the-art NLP models are now adapted from one of a few foundation models, such as BERT, RoBERTa, BART, T5, etc. How are you making your model explainable? Typical questions include: What is your model’s use case?

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Heartbeat

AUGUST 23, 2023

Enter Natural Language Processing (NLP) and its transformational power. This is the promise of NLP: to transform the way we approach legal discovery. The seemingly impossible chore of sorting through mountains of legal documents can be accomplished with astonishing efficiency and precision using NLP.

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John Snow Labs

MAY 22, 2023

After thorough research of an annotation tool for text content, they chose NLP Lab, because of its out-of-the-box pre-annotation features that allow automatic annotation of travel reviews with entities, relations, or sentiment tags. Here is how you can get started with creating your own NLP Lab project: 1.

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Mlearning.ai

FEBRUARY 6, 2023

This is why we need Explainable AI (XAI). This methodology has been used to provide explanations for sentiment classification, topic tagging, and other NLP tasks and could potentially work for chatbot-writing detection as well. 2022) Shtetl-Optimized: The Blog of Scott Aaronson. [11] And I agree to an extent. Nauta, R.v.

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Heartbeat

JULY 11, 2023

Photo by Oleg Laptev on Unsplash By improving many areas of content generation, optimization, and analysis, natural language processing (NLP) plays a crucial role in content marketing. Artificial intelligence (AI) has a subject called natural language processing (NLP) that focuses on how computers and human language interact.

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Heartbeat

NOVEMBER 7, 2023

NLP — Topic Modeling For a TV Series Episode Summary Introduction Many of us watch TV shows for leisure within our daily mundane routines via various online streaming platforms (such as Amazon Prime or Netflix), each having its share of show categories. Each episode present in the show contains a story with some difference in their nature.

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Heartbeat

NOVEMBER 21, 2023

Natural Language Processing (NLP) has experienced a transformative revolution with the advent of deep learning, empowering devices to understand, interpret, and generate human language with remarkable precision. Join us as we delve into NLP and explore how deep knowledge has increased language understanding.

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Unite.AI

AUGUST 20, 2023

Copy AI doesn't just write short-form content like social media posts or product descriptions; it also writes long-form articles and blog posts 10x faster using its powerful content generator. By the end of this blog, you will clearly understand whether Copy.ai In this review, we will dive deep into what exactly Copy.ai Chat by Copy.ai

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IBM Journey to AI blog

FEBRUARY 23, 2024

Beyond the simplistic chat bubble of conversational AI lies a complex blend of technologies, with natural language processing (NLP) taking center stage. NLP translates the user’s words into machine actions, enabling machines to understand and respond to customer inquiries accurately. What makes a good AI conversationalist?

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IBM Journey to AI blog

SEPTEMBER 20, 2023

When implemented in a responsible way—where the technology is fully governed, privacy is protected and decision making is transparent and explainable—AI has the power to usher in a new era of government services. appeared first on IBM Blog. Let’s embrace the age of AI value creation together.

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Towards AI

MARCH 31, 2024

Image by Freepik Nowadays, NLP is one of the most trending fields. This is not a surprise as NLP tools like ChatGPT are a game changer in AI. Believe me, there are transformers at the NLP center today. Today, I’ll walk you through how to create an end-to-end NLP project. Let me briefly explain this.

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Mlearning.ai

APRIL 1, 2023

NLP A Comprehensive Guide to Word2Vec, Doc2Vec, and Top2Vec for Natural Language Processing In recent years, the field of natural language processing (NLP) has seen tremendous growth, and one of the most significant developments has been the advent of word embedding techniques. I hope you find this article to be helpful.

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IBM Journey to AI blog

OCTOBER 16, 2023

The rise of the foundation model ecosystem (which is the result of decades of research in machine learning), natural language processing (NLP) and other fields, has generated a great deal of interest in computer science and AI circles. The development and use of these models explain the enormous amount of recent AI breakthroughs.

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Heartbeat

MARCH 22, 2023

Learn NLP data processing operations with NLTK, visualize data with Kangas , build a spam classifier, and track it with Comet Machine Learning Platform Photo by Stephen Phillips — Hostreviews.co.uk on Unsplash At its core, the discipline of Natural Language Processing (NLP) tries to make the human language “palatable” to computers.

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ODSC - Open Data Science

JANUARY 1, 2024

Over the years, ODSC has developed a close relationship with them, working together to host webinars, write blogs, and even collaborate on sessions at ODSC conferences. Below, you’ll find a rundown of all of our Microsoft and ODSC collaborative efforts, including past webinars & talks, blogs, and more. Where can I stay up to date?

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Artificial Corner

JULY 7, 2023

Unlocking the Power of AI Language Models through Effective Prompt Crafting Midjourney In the world of artificial intelligence (AI), one of the most exciting and rapidly evolving areas is Natural Language Processing (NLP). NLP is a branch of AI that focuses on the interaction between humans and computers using natural language.

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Explosion

JUNE 18, 2021

In this blog post, I’m going to discuss some of the biggest challenges for applied NLP and translating business problems into machine learning solutions. This blog post is based on talks I gave at the “Teaching NLP” workshop at NAACL 2021 and the L3-AI online conference. I call this “Applied NLP Thinking”.

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Ehud Reiter

MARCH 26, 2023

One of the things I most dislike about academic NLP research is the focus on leaderboards. A leaderboard is essentially a scorecard of how well different systems do on an NLP task, ie how well they perform on a fixed dataset as measured by specified evaluation metrics. I explained my dislike of leaderboards ia a previous blog.

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Towards AI

JUNE 5, 2023

In Part 1 (fine-tuning a BERT model), I explained what a transformer model is and the various open source models types that are available from Hugging Face’s free transformers library. In Part… Read the full blog for free on Medium. We also walked through how to fine-tune a BERT model to conduct sentiment analysis.

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Jay Alammar

DECEMBER 16, 2020

input saliency is a method that explains individual predictions. This is a method of attribution explaining the relationship between a model's output and inputs -- helping us detect errors and biases, and better understand the behavior of the system. Multiple methods exist for assigning importance scores to the inputs of an NLP model.

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Towards AI

FEBRUARY 13, 2023

A practical guide on how to perform NLP tasks with Hugging Face Pipelines Image by Canva With the libraries developed recently, it has become easier to perform deep learning analysis. Hugging Face is a platform that provides pre-trained language models for NLP tasks such as text classification, sentiment analysis, and more.

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Sebastian Ruder

JANUARY 24, 2022

2021) 2021 saw many exciting advances in machine learning (ML) and natural language processing (NLP). If CNNs are pre-trained the same way as transformer models, they achieve competitive performance on many NLP tasks [28].   Popularized by GPT-3 [32] , prompting has emerged as a viable alternative input format for NLP models.

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IBM Journey to AI blog

OCTOBER 16, 2023

Voice-based queries use Natural Language Processing (NLP) and sentiment analysis for speech recognition. This communication can involve speech recognition, speech-to-text conversion, NLP, or text-to-speech. Google Translate uses NLP to translate words across more than 130 languages.

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Towards AI

APRIL 2, 2024

As per the official blog, Grok-1.5 These small-scale deployments are helping to inform our approach, safeguards, and thinking about how Voice Engine could be used for good across various industries,” OpenAI said in its blog post. You can also find the notebook used in the blog. Five 5-minute reads/videos to keep you learning 1.

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IBM Journey to AI blog

AUGUST 1, 2023

Foundation models can be trained to perform tasks such as data classification, the identification of objects within images (computer vision) and natural language processing (NLP) (understanding and generating text) with a high degree of accuracy. An open-source model, Google created BERT in 2018. All watsonx.ai

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IBM Journey to AI blog

SEPTEMBER 28, 2023

included the Slate family of encoder-only models useful for enterprise NLP tasks. Trained on permissively licensed data from GitHub, the model can be used as a technical assistant, explaining, and answering general questions about code in natural language. appeared first on IBM Blog. ” The initial release of watsonx.ai

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