Towards AI

FEBRUARY 13, 2023

The NLP tasks we’ll cover are text classification, named entity recognition, question answering, and text generation. NLP is a subfield of AI that allows computers to interpret, manipulate and understand human language. Next, we give the name of the task we are interested in. Let’s dive in! What is NLP?

Python 90

Python Deep Learning Deep Learning Natural Language Processing 90

Heartbeat

JUNE 22, 2023

Sentiment analysis, language translation, and speech recognition are a few NLP applications. Tokenization, part-of-speech tagging, named entity recognition, and sentiment analysis are some of the procedures involved in this. Tokenization is the method of separating text into single phrases or words.

Natural Language Processing 59

Natural Language Processing Machine Learning Machine Learning Deep Learning 59

Pickl AI

JULY 4, 2023

Here are some common challenges associated with tokenization: Ambiguity: Ambiguity arises when a word or phrase can have multiple interpretations or meanings. Resolving ambiguity requires understanding the surrounding context or utilizing advanced techniques such as part-of-speech tagging or named entity recognition.

Natural Language Processing 52

Natural Language Processing Algorithm Machine Learning Machine Learning 52

Heartbeat

MARCH 22, 2023

Let’s see how: import nltk from nltk.tokenize import word_tokenize # Text to tokenize text_example = """We can do so much with Natural Language Processing ranging from speech recognition, recommendation systems, spam classifiers, and so many more applications."""

Natural Language Processing 52

Natural Language Processing Deep Learning Deep Learning Machine Learning 52

Defined.ai blog

AUGUST 30, 2023

Pragmatics : NLP also dives into how context influences how language is interpreted. Phonetics and Phonology : While more applicable to speech recognition, this digs into language sounds, aiding in tasks like transcription and voice-based commands. Here’s how: Pattern Recognition : ML algorithms excel at recognizing patterns.

Machine Learning 52

Machine Learning Machine Learning Natural Language Processing ML 52

Dataconomy

JANUARY 10, 2024

This innovative platform allows users to create and engage with sentient AI entities that aim to replicate real human conversation. utilizes advanced NLP techniques to understand and interpret human language. enables these AI entities to understand and generate responses that feel remarkably close to authentic human interaction.

AI 127

AI AI Artificial Intelligence Artificial Intelligence 127

Defined.ai blog

SEPTEMBER 21, 2023

In this exploration, we’ll journey deep into some Natural Language Processing examples , as well as uncover the mechanics of how machines interpret and generate human language. It’s a subfield of artificial intelligence (AI) focused on enabling machines to understand, interpret, and produce human languag e.

Natural Language Processing 52

Natural Language Processing Data Mining Data Mining Data Mining 52

Dataconomy

MARCH 14, 2023

These fields involve the use of machine learning and artificial intelligence to enable machines to understand, interpret, and generate human language. The model’s automatic speech recognition (ASR) capabilities are not limited to commonly spoken languages like English and Mandarin.

Natural Language Processing 70

Natural Language Processing Machine Learning Machine Learning Supervised Learning 70

Smart Data Collective

MAY 31, 2022

One of the most remarkable changes has been the Named Entity Recognition tool, which can differentiate between the capitalization rules of German and English. Note that annotation can interpret various file types. A number of new applications are making machine learning technology more robust than ever.

Machine Learning 106

Machine Learning Machine Learning Artificial Intelligence Artificial Intelligence 106

Dataconomy

MAY 25, 2023

By leveraging advanced algorithms and machine learning techniques, IoT devices can analyze and interpret data in real-time, enabling them to make informed decisions and take autonomous actions. By integrating AI with IoT, devices gain the ability to interpret and analyze massive amounts of data collected from sensors and other sources.

Internet of Things 160

Internet of Things Artificial Intelligence Artificial Intelligence AI 160

AssemblyAI

NOVEMBER 30, 2023

  Speech AI represents AI models that recognize, understand, and interpret speech or voice data.   Advancements in Speech AI technology have increased the accuracy of speech-to-text AI models (or Automatic Speech Recognition) to near-human levels making it possible to transcribe highly technical conversations.

AI 59

AI AI Database 59

IBM Journey to AI blog

AUGUST 28, 2023

As it pertains to social media data, text mining algorithms (and by extension, text analysis) allow businesses to extract, analyze and interpret linguistic data from comments, posts, customer reviews and other text on social media platforms and leverage those data sources to improve products, services and processes.

Machine Learning 55

Machine Learning Machine Learning Data Mining Data Mining 55

Pickl AI

MARCH 27, 2023

Natural Language Processing (NLP) focuses on enabling computers to understand, interpret, and generate human language. Named Entity Recognition NLP can be used to identify and extract named entities such as people, organizations, and locations from text data. What is NLP?

Natural Language Processing 52

Natural Language Processing Data Analysis Data Analysis Machine Learning 52

ODSC - Open Data Science

SEPTEMBER 18, 2023

This section will equip you with knowledge on how to build more advanced, robust models that can handle complex NLP tasks such as machine translation, question-answering, and named entity recognition. Large Language Models Finally, the course concludes with a look at large language models, such as BERT, ELMo, GPT, and ULMFiT.

Deep Learning 52

Deep Learning Deep Learning Machine Learning Machine Learning 52

AWS Machine Learning Blog

MAY 16, 2023

model = Model( image_uri=image_uri, model_data=model_uri, role=aws_role, predictor_cls=Predictor, name=endpoint_name, ) # Set the serializer/deserializer used to run inference through the sagemaker API. The following code creates a custom shell interpreter that can interact with your endpoint. The deploy method may take a few minutes.

AWS 84

AWS Machine Learning Machine Learning ML 84

Explosion

DECEMBER 14, 2021

Hello everyone, my name is Edward! Evaluation ✨ Section 3: Named Entity Recognition ⚙️ Section 5: Healthsea in production 3.1 We use spaCy’s built-in Named Entity Recognition and Text Classification capabilities to build and train an ML pipeline with custom-created components for Clause Segmentation and Entity Blinding.

Clustering 52

Clustering Machine Learning Machine Learning Natural Language Processing 52

ODSC - Open Data Science

JANUARY 25, 2023

Better transparency, accuracy, and accessibility to powerful ML frameworks Data scientists know that accuracy and performance are no longer the only objectives when developing machine learning systems, fairness and interpretability must be considered as well.

Machine Learning 59

Machine Learning Machine Learning Azure ML 59

Women in Big Data

DECEMBER 13, 2023

Natural Language Processing (NLP) is a branch of Artificial Intelligence (AI) that helps computers understand, interpret and manipulate human language. NLP Scientist, Linguist, NLP Data Scientist, NLP ML Engineer, Conversational AI Developer, NLP Consultant, Prompt Engineer to name a few.

Natural Language Processing 52

Natural Language Processing Big Data Big Data Computer Science 52

AssemblyAI

APRIL 15, 2024

It primarily consists of two components: Speech recognition technology: Speech recognition technology (also known as speech to text or speech to text AI) converts spoken language into text, a complex process that requires the AI to accurately identify words amidst other noises.

AI 59

AI AI Natural Language Processing Machine Learning 59

Dataconomy

JULY 26, 2023

Named Entity Recognition (NER), Sentiment Analysis, Text Classification, and Language Translation are some of the powerful tools at the disposal of contract managers. Understanding the nuances of different contracts is crucial in effectively applying NLP for contracts management and extracting meaningful insights.

Natural Language Processing 171

Natural Language Processing Artificial Intelligence Artificial Intelligence AI 171

AWS Machine Learning Blog

APRIL 3, 2023

Prompts can also help incorporate domain knowledge on specific tasks and improve interpretability. It develops insights by recognizing the entities, key phrases, language, sentiments, and other common elements in a document. Prompt engineering can greatly improve the performance of zero-shot and few-shot learning models.

Natural Language Processing 75

Natural Language Processing Machine Learning Machine Learning Algorithm 75

Dataconomy

OCTOBER 3, 2023

These platforms offer an ideal environment for delving into subjects like machine learning, image recognition, and computer vision, and yes, for a touch of entertainment as well. With just a handful of selfies, the tool can craft photorealistic portraits in diverse styles, spanning superheroes to anime interpretations.

AI 201

AI AI Machine Learning Machine Learning 201

AWS Machine Learning Blog

AUGUST 14, 2023

Prompts can also help incorporate domain knowledge on specific tasks and improve interpretability. Name]: Steve Ballmer [Position]: CEO [Company]: Microsoft ### [Text]: Franck Riboud was born on 7 November 1955 in Lyon. Name]: Fred [Position]: Co-founder and CEO [Company]: Platform.sh He is the CEO at Danone.

AWS 70

AWS Natural Language Processing Machine Learning Machine Learning 70

AssemblyAI

MARCH 8, 2023

AI art at New York’s MoMA, where a Machine Learning model interprets publicly available informational and visual data to produce the art piece, Refik Anadol: Unsupervised. An interactive AI-powered avatar named Violet, powered by the NVIDIA Omniverse Avatar Cloud Engine (ACE). Interested in more content like this?

AI 59

AI AI Machine Learning Machine Learning 59

DrivenData Labs

DECEMBER 7, 2023

Solvers submitted a wide range of methodologies to this end, including using open-source and third party LLMs (GPT, LLaMA), clustering (DBSCAN, K-Means), dimensionality reduction (PCA), topic modeling (LDA, BERT), sentence transformers, semantic search, named entity recognition, and more. What motivated you to participate? :

Natural Language Processing 130

Natural Language Processing Clustering Data Science Data Analysis 130

Mlearning.ai

JULY 23, 2023

Named Entity Recognition (NER) : Identifying and classifying named entities (such as people, places, and organizations) in text. Speech Recognition : Converting speech to text. github.com) WRITER at MLearning.ai // Code Interpreter // Animate Midjourney Mlearning.ai

Algorithm 52

Algorithm Natural Language Processing Artificial Intelligence Artificial Intelligence 52

Snorkel AI

FEBRUARY 13, 2023

If you take the Voice remote, you see this blue button in the middle, you press it, and we then stream the audio to our speech recognition system where we then translate the sound into a text query. And then, a set of parameters, in this case, CNN, as the name of the channel you want to tune to, right? But so how does it actually work?

Machine Learning 52

Machine Learning Machine Learning AI AI 52

Snorkel AI

FEBRUARY 13, 2023

If you take the Voice remote, you see this blue button in the middle, you press it, and we then stream the audio to our speech recognition system where we then translate the sound into a text query. And then, a set of parameters, in this case, CNN, as the name of the channel you want to tune to, right? But so how does it actually work?

Machine Learning 52

Machine Learning Machine Learning Deep Learning Deep Learning 52

Heartbeat

JULY 5, 2023

It interprets user input and generates suitable responses using artificial intelligence (AI) and natural language processing (NLP). The aim of NLP is to enable computers to understand, interpret, and create human language. Introduction Do you know, why chatbots have become increasingly popular in recent years?

Natural Language Processing 52

Natural Language Processing Deep Learning Deep Learning Artificial Intelligence 52

Chatbots Life

AUGUST 31, 2023

Language understanding: ChatGPT can comprehend and interpret user inputs, which can range from simple queries to more complex sentences. It’s capable of extracting intent, entities, and context from the provided text. For example: “Welcome to [Company Name] support! How can I assist you today?”

Python 52

Python AI AI 52

Google Research AI blog

DECEMBER 7, 2022

Africa-centric Transfer Learning for Named Entity Recognition David Ifeoluwa Adelani, Graham Neubig, Sebastian Ruder , Shruti Rijhwani, Michael Beukman, Chester Palen-Michel, Constantine Lignos, Jesujoba O. Alabi, Shamsuddeen H.

Natural Language Processing 52

Natural Language Processing Artificial Intelligence Artificial Intelligence Clustering 52

Chatbots Life

MAY 12, 2023

Perform various NLP tasks such as Summarization, Named Entity Recognition, Translation, Guided Text Generation As shown in the previous sections almost any NLP task can be converted to Text-to-text format. For example Named Entity Recognition can be modelled as question answering. And, as mentioned before.

AI 105

AI AI ML ML 105

Pickl AI

JULY 31, 2023

Natural Language Processing (NLP) NLP enables AI systems to understand, interpret, and generate human language. Computer Vision AI’s computer vision capabilities enable it to interpret and process visual information from images and videos. ” Key Features of Blockchain: 1. Read Blog: How to become an AI Architect?

AI 52

AI AI Artificial Intelligence Artificial Intelligence 52

DagsHub

MAY 7, 2024

The main objectives of machine learning model testing include identifying errors, evaluating performance metrics, ensuring the model’s ability to generalize across diverse datasets and avoid potential security threats, and enhancing interpretability to better understand the model’s decisions.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

DagsHub

MAY 7, 2024

The main objectives of machine learning model testing include identifying errors, evaluating performance metrics, ensuring the model’s ability to generalize across diverse datasets and avoid potential security threats, and enhancing interpretability to better understand the model’s decisions.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

AWS Machine Learning Blog

NOVEMBER 14, 2023

Claude is a generative LLM based on Anthropic’s research into creating reliable, interpretable, and steerable AI systems. has proposed the use of an encoder-decoder model using NER (named entity recognition) to mask the named entities in order to ensure that the token masked actually uses the knowledge encoded in the language model.

Computer Science 105

Computer Science Computer Science AWS Python 105

ODSC - Open Data Science

JANUARY 29, 2024

Data Science Knowing the ins and outs of data science encompasses the ability to handle, analyze, and interpret data, which is required for training models and understanding their outputs. Knowledge in these areas enables prompt engineers to understand the mechanics of language models and how to apply them effectively.

Data Science 52

Data Science Machine Learning Machine Learning AI 52