Best AI tools for< Apply Frameworks >

Kavita Ganesan's website offers a range of resources and services related to AI, including AI strategy books, tips for AI success, data science and NLP tutorials, speaking engagements, workshops, AI consulting, and more. The site aims to help businesses leverage AI to gain a competitive advantage and maximize success through proven strategies and frameworks.

Jobright.ai is a comprehensive platform that serves as the go-to place for top AI and ML jobs and companies. It provides real-time listings from major job boards and over 20,000 AI company career sites. The site is updated hourly, offering insights into various roles within the AI industry, including AI & ML engineering, AI framework, AI infrastructure, AI researcher, AI robotics, computer vision, deep learning, and more. Jobright.ai is maintained by Jobright.ai and features a wide range of job openings and AI companies for job seekers and professionals in the field.

Interview Igniter is an AI-powered platform that provides job seekers with a robust interview simulation to fine-tune their skills, adapt to their learning curve, and get detailed feedback. It offers a comprehensive question bank, including industry-specific questions and actual interview questions asked by leading tech companies like Google, Facebook, Apple, and Amazon. Interview Igniter also provides a coding interview tool for practicing and improving coding skills, with interactive guidance and tailored learning experiences. The platform utilizes Conversation Intelligence tools for analyzing communication in real-time and providing nuanced feedback. Interview Igniter was created by Vidal Graupera, a former engineering manager at LinkedIn and Uber with over 20 years of experience hiring.

This website provides a platform for users to apply artificial intelligence (AI) to their work. Users can access a variety of AI tools and resources, including pre-trained models, datasets, and tutorials. The website also provides a community forum where users can connect with other AI enthusiasts and experts.

Easy Apply is an AI-powered application designed to simplify and enhance the job search process. It offers advanced features such as AI-powered resumes and cover letters, personalized job recommendations, and a beautiful resume builder. With Easy Apply, users can auto-apply to hundreds of jobs, increasing their chances of landing their dream job. The application aims to make job hunting smarter, faster, and more efficient for job seekers.

Apply.Dog is an AI-powered tool that automates the job application process. It fills out online job applications for you, saving you time and effort. With Apply.Dog, you can focus on finding the right job for you, while we take care of the tedious task of filling out applications.

AIR is an advanced AI tool designed to streamline and optimize various tasks through the power of artificial intelligence. It leverages cutting-edge algorithms to provide users with intelligent solutions for complex problems. With a user-friendly interface and robust functionality, AIR is a versatile tool that can be used across different industries and domains.

SuperStuff.ai is an AI-powered platform that connects businesses with top marketing, creative, growth, and sales professionals. It offers a wide range of opportunities with top companies in various categories such as account management, animation, content marketing, digital marketing, influencer marketing, and more. Users can explore portfolios, book calls, and sign up to meet experts. The platform leverages AI technology to match professionals with suitable job opportunities based on their skills and preferences.

Hireintel is an AI tool designed to streamline the hiring process for companies by utilizing AI-powered interviews. The platform leverages advanced algorithms to analyze candidate responses and provide valuable insights to recruiters. By automating the initial screening process, Hireintel helps companies save time and resources while ensuring a more efficient and data-driven recruitment process.

BidPacer is an AI bidder for freelance projects that helps users generate personalized proposals and apply for freelance jobs quickly and efficiently. The application utilizes artificial intelligence to create tailored job proposals, cover letters, and job-related credentials, making the job application process seamless and time-saving. BidPacer offers a real-time job portal that lists freelance opportunities from popular platforms like Upwork, Freelancer, and Guru, enabling users to apply for jobs with just a few clicks. With features like instant job notifications, custom proposal generation, and one-click job application, BidPacer aims to enhance freelancers' productivity and job application success rates.

Jobzi is an AI-powered job application bot that helps users find and apply for jobs in the UK. It uses machine learning to search for relevant job postings and automatically fill out and submit applications on behalf of users. Jobzi also provides users with a dashboard where they can track their applications and communicate with recruiters.

JobWizard is an AI-powered tool that helps job seekers autofill job applications. It uses natural language processing and machine learning to extract information from your resume and LinkedIn profile, and then automatically fills out the corresponding fields on job applications. This can save you a lot of time and hassle, and it can also help you to avoid making mistakes that could cost you the job.

Mistral is a knowledge management tool that helps users retain, apply, and succeed in their learning endeavors. It offers features such as seamless integration with popular note-taking tools, proven learning techniques for better retention, summarization of YouTube videos and text-based content, distraction-free reading, and resource management. Mistral is designed to help users overcome the challenges of information overload, wasteful distractions, and forgetfulness, empowering them to unlock their full learning potential.

AIApply is a suite of AI-powered job search tools designed to help job seekers land their dream jobs faster and easier. The platform offers a range of services, including a job application kit, AI resume builder, AI cover letter generator, AI job interview preparation, and more. AIApply's tools are powered by advanced AI models that have been trained on the most successful cover letters and resumes that have landed candidates high-paying jobs. The platform is easy to use and affordable, making it a great option for job seekers of all levels.

AutoJobs is an AI-powered tool designed to streamline the job application process. It leverages artificial intelligence to automatically apply to job listings on behalf of users, saving time and effort. By analyzing job requirements and user profiles, AutoJobs matches candidates with suitable positions and submits applications seamlessly. With a user-friendly interface, it offers a convenient solution for job seekers looking to increase their chances of landing interviews and job offers.

JobHire is an AI-powered job search automation platform that helps users find and apply to relevant job openings. It uses artificial intelligence to analyze and recreate users' resumes, making them more attractive to potential employers. JobHire also automatically creates email addresses and uses them to send responses to suitable vacancies, modifying users' resumes for each specific position. Additionally, it tracks responses from employers and provides users with a dashboard to track their progress.

Papertalk.io is an AI-powered platform that revolutionizes research by providing users with access to over 215 million papers, AI-generated explanations, and actionable insights. The platform offers precision search tools, AI-powered understanding of research papers, and personalized guidance on applying insights practically. Papertalk.io aims to make research more accessible and approachable for users from diverse backgrounds, transforming complex data into easy-to-digest formats to foster innovation and expertise.

Instabase is an AI-native unstructured data platform that helps businesses transform their processes stuck in unstructured data. It offers solutions for automating document processing workflows, analyzing data from any document or knowledge base, and surfacing insights across all company data. Instabase leverages generative AI, agentic reasoning, and federated processing to enable users to automate processes, find information, and make smarter decisions faster. The platform prioritizes AI privacy, security, and trust, providing users with complete control over their data and enterprise-grade security measures. Instabase has received several awards and recognitions for its innovative approach to leveraging AI for business solutions.

The AI Guild is Europe's leading practitioner community in various AI-related fields such as Analytics Engineering, Data Science, Machine Learning, NLP, and more. It offers career support, exclusive connections, technical skills profiles, and growth opportunities for its members. Additionally, the AI Guild provides services for companies, including support in evaluating use cases, deploying to production, and scaling infrastructure.

Autojob is a job search automation platform that helps users find jobs faster and more efficiently. It offers a range of features, including automatic job application, job filtering, and CV optimization. Autojob is designed to save users time and effort by automating the job search process.

Ivy is an open-source machine learning framework that enables users to convert code between different ML frameworks and write framework-agnostic code. It allows users to transpile code from one framework to another, making it easy to use building blocks from different frameworks in a single project. Ivy also serves as a flexible framework that breaks free from framework limitations, allowing users to publish code that is interoperable with various frameworks and future frameworks. Users can define trainable modules and layers using Ivy's stateful API, making it easy to build and train models across different backends.

Kubeflow Training Operator is a Kubernetes-native project for fine-tuning and scalable distributed training of machine learning (ML) models created with various ML frameworks such as PyTorch, Tensorflow, XGBoost, MPI, Paddle and others. Training Operator allows you to use Kubernetes workloads to effectively train your large models via Kubernetes Custom Resources APIs or using Training Operator Python SDK. > Note: Before v1.2 release, Kubeflow Training Operator only supports TFJob on Kubernetes. * For a complete reference of the custom resource definitions, please refer to the API Definition. * TensorFlow API Definition * PyTorch API Definition * Apache MXNet API Definition * XGBoost API Definition * MPI API Definition * PaddlePaddle API Definition * For details of all-in-one operator design, please refer to the All-in-one Kubeflow Training Operator * For details on its observability, please refer to the monitoring design doc.

Katib is a Kubernetes-native project for automated machine learning (AutoML). Katib supports Hyperparameter Tuning, Early Stopping and Neural Architecture Search. Katib is the project which is agnostic to machine learning (ML) frameworks. It can tune hyperparameters of applications written in any language of the users’ choice and natively supports many ML frameworks, such as TensorFlow, Apache MXNet, PyTorch, XGBoost, and others. Katib can perform training jobs using any Kubernetes Custom Resources with out of the box support for Kubeflow Training Operator, Argo Workflows, Tekton Pipelines and many more.

Docling is a tool that bundles PDF document conversion to JSON and Markdown in an easy, self-contained package. It can convert any PDF document to JSON or Markdown format, understand detailed page layout, reading order, recover table structures, extract metadata such as title, authors, references, and language, and optionally apply OCR for scanned PDFs. The tool is designed to be stable, lightning fast, and suitable for macOS and Linux environments.

This repository contains assets related to AI/ML workloads on Google Kubernetes Engine (GKE). Run optimized AI/ML workloads with Google Kubernetes Engine (GKE) platform orchestration capabilities. A robust AI/ML platform considers the following layers: Infrastructure orchestration that support GPUs and TPUs for training and serving workloads at scale Flexible integration with distributed computing and data processing frameworks Support for multiple teams on the same infrastructure to maximize utilization of resources

CISO Assistant is a tool that helps organizations manage their cybersecurity posture and compliance. It provides a centralized platform for managing security controls, threats, and risks. CISO Assistant also includes a library of pre-built frameworks and tools to help organizations quickly and easily implement best practices.

The Generative AI Use Cases Repository showcases a wide range of applications in generative AI, including Retrieval-Augmented Generation (RAG), AI Agents, and industry-specific use cases. It provides practical notebooks and guidance on utilizing frameworks such as LlamaIndex and LangChain, and demonstrates how to integrate models from leading AI research companies like Anthropic and OpenAI.

Jina is a tool that allows users to build multimodal AI services and pipelines using cloud-native technologies. It provides a Pythonic experience for serving ML models and transitioning from local deployment to advanced orchestration frameworks like Docker-Compose, Kubernetes, or Jina AI Cloud. Users can build and serve models for any data type and deep learning framework, design high-performance services with easy scaling, serve LLM models while streaming their output, integrate with Docker containers via Executor Hub, and host on CPU/GPU using Jina AI Cloud. Jina also offers advanced orchestration and scaling capabilities, a smooth transition to the cloud, and easy scalability and concurrency features for applications. Users can deploy to their own cloud or system with Kubernetes and Docker Compose integration, and even deploy to JCloud for autoscaling and monitoring.

Awesome Mobile LLMs is a curated list of Large Language Models (LLMs) and related studies focused on mobile and embedded hardware. The repository includes information on various LLM models, deployment frameworks, benchmarking efforts, applications, multimodal LLMs, surveys on efficient LLMs, training LLMs on device, mobile-related use-cases, industry announcements, and related repositories. It aims to be a valuable resource for researchers, engineers, and practitioners interested in mobile LLMs.

LitData is a tool designed for blazingly fast, distributed streaming of training data from any cloud storage. It allows users to transform and optimize data in cloud storage environments efficiently and intuitively, supporting various data types like images, text, video, audio, geo-spatial, and multimodal data. LitData integrates smoothly with frameworks such as LitGPT and PyTorch, enabling seamless streaming of data to multiple machines. Key features include multi-GPU/multi-node support, easy data mixing, pause & resume functionality, support for profiling, memory footprint reduction, cache size configuration, and on-prem optimizations. The tool also provides benchmarks for measuring streaming speed and conversion efficiency, along with runnable templates for different data types. LitData enables infinite cloud data processing by utilizing the Lightning.ai platform to scale data processing with optimized machines.

LLMOps Duke AIPI is a course focused on operationalizing Large Language Models, teaching methodologies for developing applications using software development best practices with large language models. The course covers various topics such as generative AI concepts, setting up development environments, interacting with large language models, using local large language models, applied solutions with LLMs, extensibility using plugins and functions, retrieval augmented generation, introduction to Python web frameworks for APIs, DevOps principles, deploying machine learning APIs, LLM platforms, and final presentations. Students will learn to build, share, and present portfolios using Github, YouTube, and Linkedin, as well as develop non-linear life-long learning skills. Prerequisites include basic Linux and programming skills, with coursework available in Python or Rust. Additional resources and references are provided for further learning and exploration.

The NVIDIA TensorRT Model Optimizer is a library designed to quantize and compress deep learning models for optimized inference on GPUs. It offers state-of-the-art model optimization techniques including quantization and sparsity to reduce inference costs for generative AI models. Users can easily stack different optimization techniques to produce quantized checkpoints from torch or ONNX models. The quantized checkpoints are ready for deployment in inference frameworks like TensorRT-LLM or TensorRT, with planned integrations for NVIDIA NeMo and Megatron-LM. The tool also supports 8-bit quantization with Stable Diffusion for enterprise users on NVIDIA NIM. Model Optimizer is available for free on NVIDIA PyPI, and this repository serves as a platform for sharing examples, GPU-optimized recipes, and collecting community feedback.

This repository contains a comprehensive collection of 63 must-know Large Language Models (LLMs) interview questions. It covers topics such as the architecture of LLMs, transformer models, attention mechanisms, training processes, encoder-decoder frameworks, differences between LLMs and traditional statistical language models, handling context and long-term dependencies, transformers for parallelization, applications of LLMs, sentiment analysis, language translation, conversation AI, chatbots, and more. The readme provides detailed explanations, code examples, and insights into utilizing LLMs for various tasks.

The 'Awesome AI Guidelines' repository aims to simplify the ecosystem of guidelines, principles, codes of ethics, standards, and regulations around artificial intelligence. It provides a comprehensive collection of resources addressing ethical and societal challenges in AI systems, including high-level frameworks, principles, processes, checklists, interactive tools, industry standards initiatives, online courses, research, and industry newsletters, as well as regulations and policies from various countries. The repository serves as a valuable reference for individuals and teams designing, building, and operating AI systems to navigate the complex landscape of AI ethics and governance.

Kafka-ML is a framework designed to manage the pipeline of Tensorflow/Keras and PyTorch machine learning models on Kubernetes. It enables the design, training, and inference of ML models with datasets fed through Apache Kafka, connecting them directly to data streams like those from IoT devices. The Web UI allows easy definition of ML models without external libraries, catering to both experts and non-experts in ML/AI.

Welcome to the μLearn x Pathway Initiative, an exciting adventure into the world of Artificial Intelligence (AI)! This comprehensive course, developed in collaboration with Pathway, will empower you with the knowledge and skills needed to navigate the fascinating world of AI, with a special focus on Large Language Models (LLMs).

Albumentations is a Python library for image augmentation. Image augmentation is used in deep learning and computer vision tasks to increase the quality of trained models. The purpose of image augmentation is to create new training samples from the existing data.

This repository provides code samples in Python, C#, REST, and JavaScript for vector support in Azure AI Search. It includes demos for various languages showcasing vectorization of data, creating indexes, and querying vector data. Additionally, it offers tools like Azure AI Search Lab for experimenting with AI-enabled search scenarios in Azure and templates for deploying custom chat-with-your-data solutions. The repository also features documentation on vector search, hybrid search, creating and querying vector indexes, and REST API references for Azure AI Search and Azure OpenAI Service.

The Keras-llm-robot Web UI project is an open-source tool designed for offline deployment and testing of various open-source models from the Hugging Face website. It allows users to combine multiple models through configuration to achieve functionalities like multimodal, RAG, Agent, and more. The project consists of three main interfaces: chat interface for language models, configuration interface for loading models, and tools & agent interface for auxiliary models. Users can interact with the language model through text, voice, and image inputs, and the tool supports features like model loading, quantization, fine-tuning, role-playing, code interpretation, speech recognition, image recognition, network search engine, and function calling.

The End-to-End LLM Bootcamp is a comprehensive training program that covers the entire process of developing and deploying large language models. Participants learn to preprocess datasets, train models, optimize performance using NVIDIA technologies, understand guardrail prompts, and deploy AI pipelines using Triton Inference Server. The bootcamp includes labs, challenges, and practical applications, with a total duration of approximately 7.5 hours. It is designed for individuals interested in working with advanced language models and AI technologies.

Helps locate and apply frameworks to your problem

Transforms basic prompts for educators using the PREPARED framework from TheAIEducator.io

The intelligent investor. Analyse stocks using Warren Buffet's favourite investment framework, outlined in Benjamin Graham's famous book. Warren takes no responsibility for investment risk.

This GPT helps you understand and apply the MITRE ATT&CK Framework, whether you are familiar with the concepts or not.

Wise tech founder offering practical and creative advice on book quotes

A co pilot to help small businesses apply for loans

Apply gold-standard startup valuation and assessment methods to identify risks and gaps in your business model and product ideas.

Helps the user apply Shape Up SDL methodology.

How do "Art Worlds" apply to emergent communities of AI artists and its culture?

Biblical counseling to apply the Gospel to any situation in your life.

A tool that uses research to apply DEI principles in education. Ensure your policies, curriculum, decisions, and communications has been assessed for bias, inclusivity, and more.

Just upload a numerical dataset for classification task, will apply data analysis and machine learning steps to make a best model possible.

I'm Back Propagation, here to help you understand and apply back propagation techniques to your AI models.

Expert in non-profit organization support and grant writing. Start by uploading the grant you want to apply for.

I guide you in learning and applying Wardley Maps.

Jouw gids voor een gebruiksvriendelijke Nederlandse overheid.

Multilingual Refugee Consultant

I'm a consultant for the Australia Awards Scholarship application process.

Guides users through VA benefits and services.

Facilitates seamless employee relocation and immigration processes.