'nlp' 검색 결과

Align Python version and repo-declared dependencies (requirements.txt / environment.yml) before installing packages for NLP research code reproduction.

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Analyze text data with NLP — preprocessing, embeddings, topic modeling, sentiment, classification, and evaluation. Use when turning unstructured text into structured insight.

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NLP on clinical text — de-identification, concept extraction, phenotyping from notes, and LLM safety guardrails.

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Detect crisis signals in user content using NLP, mental health sentiment analysis, and safe intervention protocols. Implements suicide ideation detection, automated escalation, and crisis resource integration. Use for mental health apps, recovery platforms, support communities. Activate on "crisis detection", "suicide prevention", "mental health NLP", "intervention protocol". NOT for general sentiment analysis, medical diagnosis, or replacing professional help.

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Construa sistemas de IA complexos com programação declarativa, otimize prompts automaticamente, crie sistemas RAG modulares e agentes com DSPy - framework de Programação Sistemática de Modelos de Linguagem da Stanford NLP

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Deploy AI and NLP-powered detection systems to identify business email compromise attacks by analyzing writing style, behavioral patterns, and contextual anomalies that evade traditional rule-based filters.

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Data scientist v3 — ML, deep learning, NLP, CV, experimentation, MLOps

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Deploy AI and NLP-powered detection systems to identify business email compromise attacks by analyzing writing style, behavioral patterns, and contextual anomalies that evade traditional rule-based filters.

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Build complex AI systems with declarative programming, optimize prompts automatically, create modular RAG systems and agents with DSPy - Stanford NLP's framework for systematic LM programming

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Detect crisis signals in user content using NLP, mental health sentiment analysis, and safe intervention protocols. Implements suicide ideation detection, automated escalation, and crisis resource integration. Use for mental health apps, recovery platforms, support communities. Activate on "crisis detection", "suicide prevention", "mental health NLP", "intervention protocol". NOT for general sentiment analysis, medical diagnosis, or replacing professional help.

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Deploy AI and NLP-powered detection systems to identify business email compromise attacks by analyzing writing style, behavioral patterns, and contextual anomalies that evade traditional rule-based filters.

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텍스트를 AI 모델이 다루는 작은 단위로 나누고 숫자 배열로 변환합니다. 대량 처리, 맞춤 어휘 학습, 원문 위치 대응과 입력 길이 조정을 돕습니다.

• 대량 텍스트를 모델 입력으로 전처리
• 텍스트 파일로 맞춤 어휘 학습
• 예측 결과를 원문 위치에 연결

Use Hugging Face Transformers to load pretrained models, generate text, and classify text, images, or audio. Prepare model inputs, control generation settings, and fine-tune models on custom datasets with the Trainer API.

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• Prototype text, image, or audio classification
• Configure text generation and conversational responses
• Fine-tune a model on a custom dataset

Organize repeated experiments to improve models, prompts, or agent systems against measurable goals. The skill records hypotheses and lessons in a persistent tree, isolates trials, and compares promising candidates using evaluation data kept separate from development.

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• Compare repeated experiments to improve model training
• Improve an agent system's measured success rate
• Test prompt changes against a fixed evaluator

Turn news, company announcements, and policy events into scored trading inputs. Store assessments in a standard CSV file, reduce their influence over time, and combine them with signals from price indicators to support event-based strategy testing.

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• Score the potential price impact of news and announcements
• Organize historical events into a standard CSV file
• Combine event assessments with price-based trading signals

Screen AI application inputs and historical logs for prompt injection, where malicious instructions try to redirect the model. Combine pattern matching, text structure scoring, and a DeBERTa classifier to flag suspicious content and produce JSON results.

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• Screening chatbot and AI agent inputs
• Checking external text used in retrieval-based AI applications
• Auditing historical interaction logs for injection attempts

Turn cyber threat intelligence reports into a searchable library of attacker behaviors linked to MITRE ATT&CK techniques. Export structured STIX 2.1 data, a threat information exchange format, and create detection rule templates from documented activity.

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• Cataloging attacker behaviors from threat intelligence reports
• Organizing attack patterns by tactic, technique, and threat actor
• Creating detection rule templates from documented behaviors

Prepare text for language models using HuggingFace Tokenizers, which splits text into model-readable units. Train custom vocabularies, process batches, track original text positions, and configure input lengths for use with transformers.

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• Preparing large text collections for language models
• Training a tokenizer on domain-specific text
• Mapping model outputs back to original text

Use Google's APIs to review search performance, page speed, indexing status, and organic traffic. Combine real visitor measurements with search and analytics data to identify SEO issues and create reports.

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• Reviewing search clicks, impressions, and rankings
• Tracking page experience metrics over 25 weeks
• Checking whether Google has indexed specific URLs

Prepare large text collections for AI models with fast tokenizers, which split text into model inputs. Train custom vocabularies, trace tokens to original text positions, adjust input lengths, and integrate the results with transformers.

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• Tokenizing large text collections
• Training a custom vocabulary
• Mapping extracted names or answers back to original text

Build JavaScript or TypeScript applications that run text, image, and audio models in browsers or server runtimes. Guides compatible model selection, GPU or CPU execution, caching, and memory cleanup without requiring a Python server.

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• Add text classification or translation to a browser app
• Implement image classification and object detection
• Transcribe audio using JavaScript

Learn from top Kaggle solutions across text, images, time series, tabular data, and multimodal tasks that combine data types. Explore technical analyses, model settings, reusable code templates, and practical lessons to inform machine learning projects.

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• Study top solutions for a Kaggle competition
• Find proven methods for a machine learning task
• Explore reusable machine learning code templates

Learn from top Kaggle solutions across text, images, time series, tabular data, and multimodal tasks that combine data types. Explore technical analyses, model settings, reusable code templates, and practical lessons to inform machine learning projects.

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• Study top solutions for a Kaggle competition
• Find proven methods for a machine learning task
• Explore reusable machine learning code templates

评论区量化分析：对一批评论做情感分析（正/中/负占比 + 代表评论）、高频词与短语提取、 以及需求/吐槽/提问的诉求挖掘，为内容复盘和选题反哺提供数据。当用户说"评论情感分析" "评论区分析""用户在说什么""评论正负面比例""评论高频词""评论关键词""口碑分析""评论词云" "用户诉求""评论区吐槽"时使用。基于 jieba（分词）+ SnowNLP（情感）+ 社媒情感词典。

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