AI tools for sentiment analysis tutorial
Related Tools:
Feelsy
Feelsy is a social media sentiment analysis tool that helps businesses understand how their audience feels about their content. With Feelsy, businesses can track the sentiment of their Instagram comments in real-time, identify the content that resonates most with their audience, and measure the effectiveness of their social media campaigns.
ElliSense
ElliSense is an AI-powered global market sentiment analysis tool that provides real-time insights into the sentiment of various financial assets, including stocks, cryptocurrencies, and forex currencies. It analyzes thousands of data points per second from various sources, including social media, news outlets, and industry analysts, to provide accurate and up-to-date market sentiment. The tool is designed to help traders and investors make informed decisions by providing clear and easy-to-understand market insights.
PolygrAI
PolygrAI is a digital polygraph powered by AI technology that provides real-time risk assessment and sentiment analysis. The platform meticulously analyzes facial micro-expressions, body language, vocal attributes, and linguistic cues to detect behavioral fluctuations and signs of deception. By combining well-established psychology practices with advanced AI and computer vision detection, PolygrAI offers users actionable insights for decision-making processes across various applications.
Tinq.ai
Tinq.ai is a natural language processing (NLP) tool that provides a range of text analysis capabilities through its API. It offers tools for tasks such as plagiarism checking, text summarization, sentiment analysis, named entity recognition, and article extraction. Tinq.ai's API can be integrated into applications to add NLP functionality, such as content moderation, sentiment analysis, and text rewriting.
ConvoZen.AI
ConvoZen.AI is a leading AI-driven conversational intelligence platform that provides businesses with insights and tools to improve their customer interactions. The platform offers a range of features, including AI-powered insights and key moment identification, conversation sentiment analysis, automated compliance audit, agent performance management, and custom reports and analytics. ConvoZen.AI integrates with enterprise CRM, emails, and other systems to provide real-time alerts and actionable insights. The platform is designed to help businesses improve sales, customer experience, compliance, and agent performance.
EarningsCall.ai
EarningsCall.ai is an AI-powered application that provides stock earnings call summaries and insights, helping users save time and increase equity research productivity. It summarizes earnings call insights into Guidance, Strategic Updates, Risk, and Tweet, and offers a personalized Q&A section. Users can quickly discern key facts and strategic highlights from company earnings, making it easier to monitor multiple companies at once.
TakeNote
TakeNote is a cutting-edge speech-to-text AI that transforms audio and video into documents, boosting productivity and enhancing meeting experiences. Its advanced AI models provide exceptional accuracy, approaching human-level robustness and accuracy in English speech recognition. TakeNote AI empowers teams to transcribe meetings into accurate transcripts, generate precise summaries, analyze sentiment, and identify speakers, all while ensuring high levels of security and data protection.
ThirdAI
ThirdAI is a production-ready AI platform designed for enterprises, offering out-of-the-box solutions that work at scale with 10x better price performance. It provides enterprise-grade productivity tools like document search & retrieval, content creation, FAQ bots, customer live support, hyper-personalization, risk & compliance, fraud detection, anomaly detection, and PII/sensitive data redaction. The platform allows users to bring their business problems, apply on their data, and compose AI applications without the need for extensive POC cycles or manual fine-tuning. ThirdAI focuses on low latency, security, scalability, and performance, enabling business leaders to solve critical needs in weeks, not months or years.
Stockpulse
Stockpulse is an AI-powered platform that analyzes financial news and communities using Artificial Intelligence. It provides decision support for operations by collecting, filtering, and converting unstructured data into processable information. With extensive coverage of financial media sources globally, Stockpulse offers unique historical data, sentiment analysis, and AI-driven insights for various sectors in the financial markets.
Datumbox
Datumbox is a machine learning platform that offers a powerful open-source Machine Learning Framework written in Java. It provides a large collection of algorithms, models, statistical tests, and tools to power up intelligent applications. The platform enables developers to build smart software and services quickly using its REST Machine Learning API. Datumbox API offers off-the-shelf Classifiers and Natural Language Processing services for applications like Sentiment Analysis, Topic Classification, Language Detection, and more. It simplifies the process of designing and training Machine Learning models, making it easy for developers to create innovative applications.
SocialGuard
SocialGuard.co is a website that appears to be experiencing technical difficulties at the moment. The web server is down, resulting in an error code 521. Visitors are advised to try accessing the site again in a few minutes, while the website owner is recommended to contact their hosting provider for assistance. The issue seems to be related to the web server not responding, and Cloudflare services are involved in the performance and security of the website.
Kraftful
Kraftful is an AI-powered platform designed for product builders to collect, analyze, and act on user feedback efficiently. It offers features such as sentiment analysis, auto-organizing insights into projects, generating surveys, AI-powered user interviews, and feedback translation. Kraftful helps product teams save time by automating tasks like crafting user surveys, analyzing feedback, and generating user stories. The platform aims to provide actionable product insights by turning volumes of user feedback into valuable information for product development.
hoopsAI
hoopsAI is a pioneering technology company committed to empowering retail investors in the stock market. Our cutting-edge platform leverages the immense power of large language models (LLMs) to provide personalized insights. Through continuous fine-tuning, we enhance customization and precision, enabling you to make informed decisions and maximize your understanding of the markets.
MonkeeMath
MonkeeMath is an AI tool designed to scrape comments from Reddit and Stocktwits that mention stock tickers. It utilizes ChatGPT to analyze the sentiment of these comments, determining whether they are bullish or bearish on the outlook of the ticker. The data collected is then used to generate charts and tables displayed on the website. Users can create an account to view predictions and participate in a prediction mini-game to earn a spot on the MonkeeMath user leaderboard.
SupportLogic
SupportLogic is a cloud-based support experience management platform that uses AI to help businesses improve their customer support operations. The platform provides a range of features, including sentiment analysis, case routing, and quality monitoring, that can help businesses to identify and resolve customer issues quickly and efficiently. SupportLogic also offers a number of integrations with popular CRM and ticketing systems, making it easy to implement and use.
SupportLogic
SupportLogic is a Support Experience Management Platform that uses AI to help businesses improve their customer support operations. It offers a range of features, including sentiment analysis, backlog management, intelligent case routing, proactive alerts, swarming and collaboration, account health management, customer support analytics, text analytics, SLA/SLO management, quality monitoring and coaching, agent productivity, and translation. SupportLogic integrates with existing ticketing systems and apps, and can be implemented within 45 days.
VOC AI
VOC AI is a unified customer experience management platform that fuses customer insights with AI chatbot excellence. It offers various tools such as market insight, sentiment analysis, competitive analysis, product research, and customer analytics for Amazon sellers. The platform helps users understand customer needs, preferences, and market trends to develop better products and services. VOC AI also provides AI chatbots powered by OpenAI, trained on user data to ensure precise responses and prevent misleading answers. With features like social listening, sentiment analysis, and review analysis, VOC AI empowers businesses to transform customer relationships and boost growth and profitability.
Zenus AI
Zenus AI is a behavioral analytics tool for events and retail, offering facial analysis and custom solutions for event organizers, retail brands, and exhibitors. The tool provides insights such as demographics, sentiment analysis, and behavioral tracking with 95% accuracy without collecting personal data. It helps businesses understand consumers, attract more exhibitors, and improve visitor experience through AI-powered solutions.
Syncly
Syncly is an AI-powered customer feedback analysis tool that helps businesses understand their customers' needs and improve their customer experience. With Syncly, businesses can categorize feedback, identify negative signals, and prioritize issues to resolve. Syncly also integrates with other business tools, making it easy to manage all customer feedback in one place.
Financial Sentiment Analyst
A sentiment analysis tool for evaluating management-related texts.
💹 AI Trading Sentiment Surge
AI Trading Sentiment Surge - Dive into market trends with AI-powered sentiment analysis and NLP to guide investment strategies. 🌐📊🤖
Capital Companion
A savvy guide for financial insights and strategies, including fundamental, technical, and sentiment analysis for investing and trading.
Meeting Mate
AI Meeting Analyst: Summarizes transcripts, extracts key points and action items, conducts sentiment analysis. Offers advice and insights on meeting content, objectives, and outcomes for improved effectiveness.
PitchAndBusinessPlanReviewGPT
This GPT reviews business plans and pitch decks—Please note: This GPT does NOT share information for training in GPT models. It is responsible for assigning scores and providing feedback based on key criteria such as team background, financial projections, as well as conducting sentiment analysis.
Prévisions Cryptos
Prédictif des tendances crypto à partir de la presse et des réseaux sociaux
Debunkinator
Débunker d'infos, vérificateur de photos, avec analyse de sentiments, résumés automatiques, alertes personnalisées, cartographie des sources et éducation aux médias.
Global Social Media Sage
Expert in analyzing social media for market trends, brand reputation, and consumer sentiment.
News Bias Analyzer
Fetch and Analyze the Latest News! 📊💡 Get unbiased summaries, detailed bias graphs, and engaging word clouds. Dive into the world of news with a fresh perspective! 🌍📰 Our upgraded News Bias Analyzer GPT is your go-to for insightful analysis of the latest headlines and in-depth articles.
Awesome-TimeSeries-SpatioTemporal-LM-LLM
Awesome-TimeSeries-SpatioTemporal-LM-LLM is a curated list of Large (Language) Models and Foundation Models for Temporal Data, including Time Series, Spatio-temporal, and Event Data. The repository aims to summarize recent advances in Large Models and Foundation Models for Time Series and Spatio-Temporal Data with resources such as papers, code, and data. It covers various applications like General Time Series Analysis, Transportation, Finance, Healthcare, Event Analysis, Climate, Video Data, and more. The repository also includes related resources, surveys, and papers on Large Language Models, Foundation Models, and their applications in AIOps.
LLMeBench
LLMeBench is a flexible framework designed for accelerating benchmarking of Large Language Models (LLMs) in the field of Natural Language Processing (NLP). It supports evaluation of various NLP tasks using model providers like OpenAI, HuggingFace Inference API, and Petals. The framework is customizable for different NLP tasks, LLM models, and datasets across multiple languages. It features extensive caching capabilities, supports zero- and few-shot learning paradigms, and allows on-the-fly dataset download and caching. LLMeBench is open-source and continuously expanding to support new models accessible through APIs.
HuggingFaceGuidedTourForMac
HuggingFaceGuidedTourForMac is a guided tour on how to install optimized pytorch and optionally Apple's new MLX, JAX, and TensorFlow on Apple Silicon Macs. The repository provides steps to install homebrew, pytorch with MPS support, MLX, JAX, TensorFlow, and Jupyter lab. It also includes instructions on running large language models using HuggingFace transformers. The repository aims to help users set up their Macs for deep learning experiments with optimized performance.
nlp-llms-resources
The 'nlp-llms-resources' repository is a comprehensive resource list for Natural Language Processing (NLP) and Large Language Models (LLMs). It covers a wide range of topics including traditional NLP datasets, data acquisition, libraries for NLP, neural networks, sentiment analysis, optical character recognition, information extraction, semantics, topic modeling, multilingual NLP, domain-specific LLMs, vector databases, ethics, costing, books, courses, surveys, aggregators, newsletters, papers, conferences, and societies. The repository provides valuable information and resources for individuals interested in NLP and LLMs.
hezar
Hezar is an all-in-one AI library designed specifically for the Persian community. It brings together various AI models and tools, making it easy to use AI with just a few lines of code. The library seamlessly integrates with Hugging Face Hub, offering a developer-friendly interface and task-based model interface. In addition to models, Hezar provides tools like word embeddings, tokenizers, feature extractors, and more. It also includes supplementary ML tools for deployment, benchmarking, and optimization.
spark-nlp
Spark NLP is a state-of-the-art Natural Language Processing library built on top of Apache Spark. It provides simple, performant, and accurate NLP annotations for machine learning pipelines that scale easily in a distributed environment. Spark NLP comes with 36000+ pretrained pipelines and models in more than 200+ languages. It offers tasks such as Tokenization, Word Segmentation, Part-of-Speech Tagging, Named Entity Recognition, Dependency Parsing, Spell Checking, Text Classification, Sentiment Analysis, Token Classification, Machine Translation, Summarization, Question Answering, Table Question Answering, Text Generation, Image Classification, Image to Text (captioning), Automatic Speech Recognition, Zero-Shot Learning, and many more NLP tasks. Spark NLP is the only open-source NLP library in production that offers state-of-the-art transformers such as BERT, CamemBERT, ALBERT, ELECTRA, XLNet, DistilBERT, RoBERTa, DeBERTa, XLM-RoBERTa, Longformer, ELMO, Universal Sentence Encoder, Llama-2, M2M100, BART, Instructor, E5, Google T5, MarianMT, OpenAI GPT2, Vision Transformers (ViT), OpenAI Whisper, and many more not only to Python and R, but also to JVM ecosystem (Java, Scala, and Kotlin) at scale by extending Apache Spark natively.
LLM-PowerHouse-A-Curated-Guide-for-Large-Language-Models-with-Custom-Training-and-Inferencing
LLM-PowerHouse is a comprehensive and curated guide designed to empower developers, researchers, and enthusiasts to harness the true capabilities of Large Language Models (LLMs) and build intelligent applications that push the boundaries of natural language understanding. This GitHub repository provides in-depth articles, codebase mastery, LLM PlayLab, and resources for cost analysis and network visualization. It covers various aspects of LLMs, including NLP, models, training, evaluation metrics, open LLMs, and more. The repository also includes a collection of code examples and tutorials to help users build and deploy LLM-based applications.
Awesome-LLM-Interpretability
Awesome-LLM-Interpretability is a curated list of materials related to LLM (Large Language Models) interpretability, covering tutorials, code libraries, surveys, videos, papers, and blogs. It includes resources on transformer mechanistic interpretability, visualization, interventions, probing, fine-tuning, feature representation, learning dynamics, knowledge editing, hallucination detection, and redundancy analysis. The repository aims to provide a comprehensive overview of tools, techniques, and methods for understanding and interpreting the inner workings of large language models.
awesome-openvino
Awesome OpenVINO is a curated list of AI projects based on the OpenVINO toolkit, offering a rich assortment of projects, libraries, and tutorials covering various topics like model optimization, deployment, and real-world applications across industries. It serves as a valuable resource continuously updated to maximize the potential of OpenVINO in projects, featuring projects like Stable Diffusion web UI, Visioncom, FastSD CPU, OpenVINO AI Plugins for GIMP, and more.
GenAI_Agents
GenAI Agents is a comprehensive repository for developing and implementing Generative AI (GenAI) agents, ranging from simple conversational bots to complex multi-agent systems. It serves as a valuable resource for learning, building, and sharing GenAI agents, offering tutorials, implementations, and a platform for showcasing innovative agent creations. The repository covers a wide range of agent architectures and applications, providing step-by-step tutorials, ready-to-use implementations, and regular updates on advancements in GenAI technology.
obsei
Obsei is an open-source, low-code, AI powered automation tool that consists of an Observer to collect unstructured data from various sources, an Analyzer to analyze the collected data with various AI tasks, and an Informer to send analyzed data to various destinations. The tool is suitable for scheduled jobs or serverless applications as all Observers can store their state in databases. Obsei is still in alpha stage, so caution is advised when using it in production. The tool can be used for social listening, alerting/notification, automatic customer issue creation, extraction of deeper insights from feedbacks, market research, dataset creation for various AI tasks, and more based on creativity.
ai_projects
This repository contains a collection of AI projects covering various areas of machine learning. Each project is accompanied by detailed articles on the associated blog sciblog. Projects range from introductory topics like Convolutional Neural Networks and Transfer Learning to advanced topics like Fraud Detection and Recommendation Systems. The repository also includes tutorials on data generation, distributed training, natural language processing, and time series forecasting. Additionally, it features visualization projects such as football match visualization using Datashader.
Prompt-Engineering-Holy-Grail
The Prompt Engineering Holy Grail repository is a curated resource for prompt engineering enthusiasts, providing essential resources, tools, templates, and best practices to support learning and working in prompt engineering. It covers a wide range of topics related to prompt engineering, from beginner fundamentals to advanced techniques, and includes sections on learning resources, online courses, books, prompt generation tools, prompt management platforms, prompt testing and experimentation, prompt crafting libraries, prompt libraries and datasets, prompt engineering communities, freelance and job opportunities, contributing guidelines, code of conduct, support for the project, and contact information.
spacy-llm
This package integrates Large Language Models (LLMs) into spaCy, featuring a modular system for **fast prototyping** and **prompting** , and turning unstructured responses into **robust outputs** for various NLP tasks, **no training data** required. It supports open-source LLMs hosted on Hugging Face 🤗: Falcon, Dolly, Llama 2, OpenLLaMA, StableLM, Mistral. Integration with LangChain 🦜️🔗 - all `langchain` models and features can be used in `spacy-llm`. Tasks available out of the box: Named Entity Recognition, Text classification, Lemmatization, Relationship extraction, Sentiment analysis, Span categorization, Summarization, Entity linking, Translation, Raw prompt execution for maximum flexibility. Soon: Semantic role labeling. Easy implementation of **your own functions** via spaCy's registry for custom prompting, parsing and model integrations. For an example, see here. Map-reduce approach for splitting prompts too long for LLM's context window and fusing the results back together
Awesome-LLM-Large-Language-Models-Notes
Awesome-LLM-Large-Language-Models-Notes is a repository that provides a comprehensive collection of information on various Large Language Models (LLMs) classified by year, size, and name. It includes details on known LLM models, their papers, implementations, and specific characteristics. The repository also covers LLM models classified by architecture, must-read papers, blog articles, tutorials, and implementations from scratch. It serves as a valuable resource for individuals interested in understanding and working with LLMs in the field of Natural Language Processing (NLP).
intel-extension-for-transformers
Intel® Extension for Transformers is an innovative toolkit designed to accelerate GenAI/LLM everywhere with the optimal performance of Transformer-based models on various Intel platforms, including Intel Gaudi2, Intel CPU, and Intel GPU. The toolkit provides the below key features and examples: * Seamless user experience of model compressions on Transformer-based models by extending [Hugging Face transformers](https://github.com/huggingface/transformers) APIs and leveraging [Intel® Neural Compressor](https://github.com/intel/neural-compressor) * Advanced software optimizations and unique compression-aware runtime (released with NeurIPS 2022's paper [Fast Distilbert on CPUs](https://arxiv.org/abs/2211.07715) and [QuaLA-MiniLM: a Quantized Length Adaptive MiniLM](https://arxiv.org/abs/2210.17114), and NeurIPS 2021's paper [Prune Once for All: Sparse Pre-Trained Language Models](https://arxiv.org/abs/2111.05754)) * Optimized Transformer-based model packages such as [Stable Diffusion](examples/huggingface/pytorch/text-to-image/deployment/stable_diffusion), [GPT-J-6B](examples/huggingface/pytorch/text-generation/deployment), [GPT-NEOX](examples/huggingface/pytorch/language-modeling/quantization#2-validated-model-list), [BLOOM-176B](examples/huggingface/pytorch/language-modeling/inference#BLOOM-176B), [T5](examples/huggingface/pytorch/summarization/quantization#2-validated-model-list), [Flan-T5](examples/huggingface/pytorch/summarization/quantization#2-validated-model-list), and end-to-end workflows such as [SetFit-based text classification](docs/tutorials/pytorch/text-classification/SetFit_model_compression_AGNews.ipynb) and [document level sentiment analysis (DLSA)](workflows/dlsa) * [NeuralChat](intel_extension_for_transformers/neural_chat), a customizable chatbot framework to create your own chatbot within minutes by leveraging a rich set of [plugins](https://github.com/intel/intel-extension-for-transformers/blob/main/intel_extension_for_transformers/neural_chat/docs/advanced_features.md) such as [Knowledge Retrieval](./intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/README.md), [Speech Interaction](./intel_extension_for_transformers/neural_chat/pipeline/plugins/audio/README.md), [Query Caching](./intel_extension_for_transformers/neural_chat/pipeline/plugins/caching/README.md), and [Security Guardrail](./intel_extension_for_transformers/neural_chat/pipeline/plugins/security/README.md). This framework supports Intel Gaudi2/CPU/GPU. * [Inference](https://github.com/intel/neural-speed/tree/main) of Large Language Model (LLM) in pure C/C++ with weight-only quantization kernels for Intel CPU and Intel GPU (TBD), supporting [GPT-NEOX](https://github.com/intel/neural-speed/tree/main/neural_speed/models/gptneox), [LLAMA](https://github.com/intel/neural-speed/tree/main/neural_speed/models/llama), [MPT](https://github.com/intel/neural-speed/tree/main/neural_speed/models/mpt), [FALCON](https://github.com/intel/neural-speed/tree/main/neural_speed/models/falcon), [BLOOM-7B](https://github.com/intel/neural-speed/tree/main/neural_speed/models/bloom), [OPT](https://github.com/intel/neural-speed/tree/main/neural_speed/models/opt), [ChatGLM2-6B](https://github.com/intel/neural-speed/tree/main/neural_speed/models/chatglm), [GPT-J-6B](https://github.com/intel/neural-speed/tree/main/neural_speed/models/gptj), and [Dolly-v2-3B](https://github.com/intel/neural-speed/tree/main/neural_speed/models/gptneox). Support AMX, VNNI, AVX512F and AVX2 instruction set. We've boosted the performance of Intel CPUs, with a particular focus on the 4th generation Intel Xeon Scalable processor, codenamed [Sapphire Rapids](https://www.intel.com/content/www/us/en/products/docs/processors/xeon-accelerated/4th-gen-xeon-scalable-processors.html).
ailia-models
The collection of pre-trained, state-of-the-art AI models. ailia SDK is a self-contained, cross-platform, high-speed inference SDK for AI. The ailia SDK provides a consistent C++ API across Windows, Mac, Linux, iOS, Android, Jetson, and Raspberry Pi platforms. It also supports Unity (C#), Python, Rust, Flutter(Dart) and JNI for efficient AI implementation. The ailia SDK makes extensive use of the GPU through Vulkan and Metal to enable accelerated computing. # Supported models 323 models as of April 8th, 2024
100days_AI
The 100 Days in AI repository provides a comprehensive roadmap for individuals to learn Artificial Intelligence over a period of 100 days. It covers topics ranging from basic programming in Python to advanced concepts in AI, including machine learning, deep learning, and specialized AI topics. The repository includes daily tasks, resources, and exercises to ensure a structured learning experience. By following this roadmap, users can gain a solid understanding of AI and be prepared to work on real-world AI projects.
Comment Explorer
Comment Explorer is a free tool that allows users to analyze comments on YouTube videos. Users can gain insights into audience engagement, sentiment, and top subjects of discussion. The tool helps content creators understand the impact of their videos and improve interaction with viewers.