AWS Machine Learning Blog

OCTOBER 30, 2024

Sentence transformers are powerful deep learning models that convert sentences into high-quality, fixed-length embeddings, capturing their semantic meaning. These embeddings are useful for various natural language processing (NLP) tasks such as text classification, clustering, semantic search, and information retrieval. str.split("|").str[0]

BERT 90

BERT Categorization Data Scientist Machine Learning 90

Becoming Human

MARCH 12, 2024

Automated document analysis AI tools designed for law firms use advanced technologies like NLP and machine learning to analyze extensive legal documents swiftly. Legal language processing AI-powered legal language processing simplifies legal jargon, using NLP algorithms to make legal documents more accessible.

Automation 105

Automation NLP Artificial Intelligence Artificial Intelligence 105

The MLOps Blog

FEBRUARY 15, 2024

Due to the rise of LLMs and the shift towards pre-trained models and prompt engineering, specialists in traditional NLP approaches are particularly at risk. Data scientists and NLP specialists can move towards analytical roles or into engineering to stay relevant. Are LLMs entirely overtaking AI and natural language processing (NLP)?

NLP 59

NLP Natural Language Processing Data Scientist Software Engineer 59

Mlearning.ai

JULY 31, 2023

It handles everything from initial creation of the model to successful deployment and continuous learning. DevOps aims to streamline the development and operation of software applications, while MLOps focuses on the machine learning lifecycle. Extension Of Devops MLOps is an extension of DevOps.

DevOps 52

DevOps Machine Learning Data Scientist NLP 52

Viso.ai

MARCH 26, 2024

This enhances the interpretability of AI systems for applications in computer vision and natural language processing (NLP). The introduction of the Transformer model was a significant leap forward for the concept of attention in deep learning. This is especially beneficial in NLP tasks like image captioning and video understanding.

Deep Learning 52

Deep Learning Computer Vision Neural Network Natural Language Processing 52

Sebastian Ruder

DECEMBER 6, 2021

Reading Comprehension assumes a gold paragraph is provided Standard approaches for reading comprehension build on pre-trained models such as BERT. Using BERT for reading comprehension involves fine-tuning it to predict a) whether a question is answerable and b) whether each token is the start and end of an answer span.

BERT 52

BERT NLP Natural Language Processing Computational Linguistics 52

Snorkel AI

OCTOBER 4, 2023

Instead of the rule-based decision-making of traditional credit scoring, AI can continually learn and adapt, improving accuracy and efficiency. Data teams can fine-tune LLMs like BERT, GPT-3.5 Expand data points to paint a broader financial picture. Speed and enhance model development for specific use cases.

Data Scientist 52

Data Scientist AI AI Neural Network 52

Viso.ai

APRIL 4, 2024

Continuous Learning and Adaptive Models: Online learning continuously updates the model as new data becomes available. On the other hand, transfer learning may help by adapting the model trained to do one task to do a related task. Versioning ensures that new updates can be tracked and managed.

Data Drift 52

Data Drift Computer Vision Machine Learning Algorithm 52

Pickl AI

SEPTEMBER 23, 2024

Natural Language Processing: NLP helps machines understand and generate human language, enabling technologies like chatbots and translation. To stay ahead in these dynamic fields, emphasise continuous learning and practical experience. Live DoubtBuster Sessions: Real-time support to clarify doubts and enhance learning.

Data Science 52

Data Science Artificial Intelligence Artificial Intelligence Machine Learning 52

The MLOps Blog

JANUARY 30, 2025

Its also an obstacle to continue model training later. Weight decay has been applied to transformer-based NLP models since the beginning. It is part of the open-source Ray framework for scaling machine-learning applications. Ray Tune is a hyperparameter tuning library that supports population-based training. validation loss).

LLM 64

LLM Machine Learning Large Language Models Deep Learning 64

Viso.ai

JANUARY 2, 2024

BERT, LaMDA, Claude 2, etc. The lack of continuous learning means its stock of information will soon be obsolete, and users must be careful when using the model to extract factual data. Guide to understanding and using deep learning models Deploy Deep Learning with viso.ai Alternatives include ChatGPT 4.0,

Deep Learning 52

Deep Learning Large Language Models Computer Vision Neural Network 52

ODSC - Open Data Science

NOVEMBER 4, 2024

BERT being distilled into DistilBERT) and task-specific distillation which fine-tunes a smaller model using specific task data (e.g. As AI continues to evolve, staying updated with the latest techniques is crucial. Whether it’s new optimization methods or emerging deployment tools, continuous learning is part of the process.

Prompt Engineering 52

Prompt Engineering Prompt Engineer BERT Large Language Models 52