Unite.AI

NOVEMBER 8, 2023

Natural Language Processing (NLP) has experienced some of the most impactful breakthroughs in recent years, primarily due to the the transformer architecture. GPT : Is generative in nature and can be prompted to perform tasks with minimal changes to its structure. One-hot encoding is a prime example of this limitation.

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Marktechpost

OCTOBER 15, 2024

XAI, or Explainable AI, brings about a paradigm shift in neural networks that emphasizes the need to explain the decision-making processes of neural networks, which are well-known black boxes. Quanda differs from its contemporaries, like Captum, TransformerLens, Alibi Explain, etc.,

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IBM Journey to AI blog

AUGUST 1, 2023

A foundation model is built on a neural network model architecture to process information much like the human brain does. They can also perform self-supervised learning to generalize and apply their knowledge to new tasks. The platform comprises three powerful products: The watsonx.ai

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AWS Machine Learning Blog

FEBRUARY 12, 2024

Essential ML capabilities such as hyperparameter tuning and model explainability were lacking on premises. In both cases, the evaluation and explainability report, if generated, are recorded in the model registry. Explain – SageMaker Clarify generates an explainability report. AWS_ACCOUNT] region = eu-central-1.

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ML Explainability Machine Learning Deep Learning 138

Artificial Corner

JULY 30, 2023

In this world of complex terminologies, someone who wants to explain Large Language Models (LLMs) to some non-tech guy is a difficult task. So that’s why I tried in this article to explain LLM in simple or to say general language. Natural Language Processing (NLP) is a subfield of artificial intelligence.

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Large Language Models LLM Natural Language Processing Deep Learning 87

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. Also, conversational AI systems can manage and categorize support tickets, prioritizing them based on urgency and relevance.

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Marktechpost

JULY 4, 2023

Natural language processing (NLP) activities, including speech-to-text, sentiment analysis, text summarization, spell-checking, token categorization, etc., rely on Language Models as their foundation. Unigrams, N-grams, exponential, and neural networks are valid forms for the Language Model.

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Large Language Models BERT Natural Language Processing Categorization 105

AWS Machine Learning Blog

MARCH 13, 2024

The LLM analysis provides a violation result (Y or N) and explains the rationale behind the model’s decision regarding policy violation. The Anthropic Claude V2 model delivers responses in the instructed format (Y or N), along with an analysis explaining why it thinks the message violates the policy.

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LLM Natural Language Processing Prompt Engineer Prompt Engineering 139

Topbots

JUNE 22, 2023

SA is a very widespread Natural Language Processing (NLP). So, to make a viable comparison, I had to: Categorize the dataset scores into Positive , Neutral , or Negative labels. Interestingly, ChatGPT tended to categorize most of these neutral sentences as positive. finance, entertainment, psychology).

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Machine Learning ChatGPT Natural Language Processing Categorization 107

AWS Machine Learning Blog

OCTOBER 9, 2023

In this use case, we have a set of synthesized product reviews that we want to analyze for sentiments and categorize the reviews by product type, to make it easy to draw patterns and trends that can help business stakeholders make better informed decisions. Next, we explain how to review the trained model for performance.

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Mlearning.ai

JULY 23, 2023

Introducing Natural Language Processing (NLP) , a branch of artificial intelligence (AI) specifically designed to give computers the ability to understand text and spoken words in much the same way as human beings. Text Classification : Categorizing text into predefined categories based on its content. How it works?

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Marktechpost

OCTOBER 18, 2023

Surprisingly, recent developments in self-supervised learning, foundation models for computer vision and natural language processing, and deep understanding have significantly increased data efficiency. However, most training datasets in the present literature on treatments have small sample sizes.

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Heartbeat

SEPTEMBER 7, 2023

In the ever-evolving landscape of machine learning and artificial intelligence, understanding and explaining the decisions made by models have become paramount. Enter Comet , that streamlines the model development process and strongly emphasizes model interpretability and explainability. Why Does It Matter?

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Flipboard

FEBRUARY 16, 2023

Natural language processing ( NLP ), while hardly a new discipline, has catapulted into the public consciousness these past few months thanks in large part to the generative AI hype train that is ChatGPT. million ($2.9

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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. Natural language processing: Helps computers understand and generate human language, powering chatbots, and machine translation.

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IBM Journey to AI blog

APRIL 18, 2024

While these large language model (LLM) technologies might seem like it sometimes, it’s important to understand that they are not the thinking machines promised by science fiction. Achieving these feats is accomplished through a combination of sophisticated algorithms, natural language processing (NLP) and computer science principles.

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AWS Machine Learning Blog

JANUARY 17, 2023

In this solution, we train and deploy a churn prediction model that uses a state-of-the-art natural language processing (NLP) model to find useful signals in text. In addition to textual inputs, this model uses traditional structured data inputs such as numerical and categorical fields.

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Categorization BERT Machine Learning Neural Network 94

Flipboard

OCTOBER 25, 2023

Why it’s challenging to process and manage unstructured data Unstructured data makes up a large proportion of the data in the enterprise that can’t be stored in a traditional relational database management systems (RDBMS). Understanding the data, categorizing it, storing it, and extracting insights from it can be challenging.

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AWS Machine Learning Blog

DECEMBER 23, 2024

In this post, we explore why GraphRAG is more comprehensive and explainable than vector RAG alone, and how you can use this approach using AWS services and Lettria. Lettrias in-house team manually assessed the answers with a detailed evaluation grid, categorizing results as correct, partially correct (acceptable or not), or incorrect.

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Generative AI Natural Language Processing Prompt Engineer Prompt Engineering 92

IBM Journey to AI blog

OCTOBER 16, 2023

Voice-based queries use Natural Language Processing (NLP) and sentiment analysis for speech recognition. For instance, email management automation tools such as Levity use ML to identify and categorize emails as they come in using text classification algorithms. The platform has three powerful components: the watsonx.ai

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AWS Machine Learning Blog

JANUARY 30, 2023

From image and speech recognition to natural language processing and predictive analytics, ML models have been applied to a wide range of problems. If your predictors include categorical features, you can provide a JSON file named cat_index.json in the same location as your training data.

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Pickl AI

SEPTEMBER 17, 2024

Explain The Concept of Supervised and Unsupervised Learning. It involves tasks such as handling missing values, removing outliers, encoding categorical variables, and scaling numerical features. Explain The Concept of Overfitting and Underfitting In Machine Learning Models.

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Towards AI

FEBRUARY 13, 2023

Let me explain. Zero-Shot Classification Imagine you want to categorize unlabeled text. Transformers is a library in Hugging Face that provides APIs and tools. It allows you to easily download and train state-of-the-art pre-trained models. You may ask what pre-trained models are. Let’s have a look at a few of these.

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Heartbeat

OCTOBER 11, 2023

Supervised, unsupervised, and reinforcement learning : Machine learning can be categorized into different types based on the learning approach. Interpretability and Explainability: Deep neural networks are one machine learning model that can be very complex and difficult to assess.

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Heartbeat

FEBRUARY 2, 2024

Visual Question Answering (VQA) stands at the intersection of computer vision and natural language processing, posing a unique and complex challenge for artificial intelligence. is a significant benchmark dataset in computer vision and natural language processing. or Visual Question Answering version 2.0,

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Heartbeat

JUNE 22, 2023

Yet not all chatbots are made equal, and some are more adept than others in deciphering and answering natural language questions. Natural language processing (NLP) can help with this. Recognition of named entities , such as individuals, locations, and organizations, involves identifying and categorizing them.

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NLP Chatbots Natural Language Processing Machine Learning 59

Snorkel AI

MARCH 1, 2023

This process results in generalized models capable of a wide variety of tasks, such as image classification, natural language processing, and question-answering, with remarkable accuracy. This can make it challenging for businesses to explain or justify their decisions to customers or regulators.

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John Snow Labs

APRIL 30, 2024

Named Entity Recognition (NER) is a pivotal tool in understanding documents because it identifies and categorizes specific entities mentioned within the text. It streamlines tasks such as information retrieval, summarization, and knowledge extraction, enhancing the efficiency of various natural language processing applications.

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NLP Categorization Natural Language Processing Explainability 52

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? However, in this sea of complexity, NLP offers a ray of hope.

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NLP Natural Language Processing Algorithm Categorization 52

Marktechpost

JULY 17, 2023

Using causal graphs, LIME, Shapley, and the decision tree surrogate approach, the organization also provides various features to make it easier to develop explainability into predictive analytics models. When necessary, the platform also enables numerous governance and explainability elements.

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Data Mining Machine Learning Data Scientist Artificial Intelligence 98

AWS Machine Learning Blog

SEPTEMBER 23, 2024

You can also ask Amazon Q Developer to explain existing code and troubleshoot for common errors. The dataset provided has a number of categorical features, which need to be converted to numerical features, as well as missing data. Just choose the cell with the error and enter /fix in the chat. You can find Pranav on LinkedIn.

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Heartbeat

AUGUST 29, 2023

While integrating deep learning into software development can be difficult, it has made significant progress in several fields, including computer vision, natural language processing, and speech recognition. Speech and Audio Processing : Speaker identification, speech recognition, creation of music, etc.

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Becoming Human

MAY 12, 2023

In order to develop training data for AI and machine learning, there are several types of image annotation as explained below: Bounding Box Annotation As a type of image annotation technique, bounding box annotation is used to outline the boundaries of objects. In this process, a box is drawn around the object and a label is applied.

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AWS Machine Learning Blog

OCTOBER 24, 2023

Solution overview The following diagram is a high-level reference architecture that explains how you can further enhance an IDP workflow with foundation models. Amazon Comprehend is a natural language processing (NLP) service that uses ML to extract insights from text.

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Viso.ai

MARCH 26, 2024

This enhances the interpretability of AI systems for applications in computer vision and natural language processing (NLP). Furthermore, attention mechanisms work to enhance the explainability or interpretability of AI models. In a way, you can consider it offering a window into the “thought processes” of AI.

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Deep Learning Computer Vision Neural Network Natural Language Processing 52

Pickl AI

JULY 17, 2023

Unsupervised learning helps in finding the features which are useful for categorization It takes place in real-time, which implies that all the input data is essential to be analyzed and labeled in the presence of the users. It employs unsupervised learning to categorize articles on the same news story from different online news outlets.

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Heartbeat

AUGUST 21, 2023

AlexNet was created to categorize photos in the ImageNet dataset, which contains approximately 1 million images divided into 1,000 categories. Natural Language Processing : CNNs have been implemented for sentiment analysis and text categorization in natural language processing jobs.

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