Best AI tools for< Optimize Ml Algorithms >
20 - AI tool Sites
Kofluence
Kofluence is a disruptive AI-powered Ad-Tech influencer marketing platform that empowers both brands and influencers to capitalize on the value of their social influence. With features like data-driven performance, matchmaking through AI, end-to-end campaign management, real-time performance metrics, and integration with marketing tools, Kofluence offers a comprehensive solution for effective influencer marketing campaigns. The platform boasts a vast network of over 650,000 creators, deep profiling capabilities, AI/ML algorithms, and proprietary risk and fraud detection mechanisms to ensure successful and optimized campaigns.
Tübingen AI Center
Tübingen AI Center is a thriving hub for European AI, hosted by the Eberhard Karls University of Tübingen in cooperation with the Max Planck Institute for Intelligent Systems. It comprises 20 world-class machine learning research groups with more than 300 PhD students and Postdocs. The center fosters AI talents by offering education and hands-on experience from elementary school onwards. The Machine Learning Cloud at Tübingen AI Center provides cutting-edge AI research infrastructure, supporting collaborative work and large-scale simulations in ML. Funded by the Federal Ministry of Education and Research and the Ministry of Science, Research and Arts Baden-Württemberg.
BCT Digital
BCT Digital is an AI-powered risk management suite provider that offers a range of products to help enterprises optimize their core Governance, Risk, and Compliance (GRC) processes. The rt360 suite leverages next-generation technologies, sophisticated AI/ML models, data-driven algorithms, and predictive analytics to assist organizations in managing various risks effectively. BCT Digital's solutions cater to the financial sector, providing tools for credit risk monitoring, early warning systems, model risk management, environmental, social, and governance (ESG) risk assessment, and more.
Reality AI Software
Reality AI Software is an Edge AI software development environment that combines advanced signal processing, machine learning, and anomaly detection on every MCU/MPU Renesas core. The software is underpinned by the proprietary Reality AI ML algorithm that delivers accurate and fully explainable results supporting diverse applications. It enables features like equipment monitoring, predictive maintenance, and sensing user behavior and the surrounding environment with minimal impact on the Bill of Materials (BoM). Reality AI software running on Renesas processors helps deliver endpoint intelligence in products across various markets.
OpenCV
OpenCV is the world's largest computer vision library. It's open source, contains over 2500 algorithms and is operated by the non-profit Open Source Vision Foundation.
PoplarML
PoplarML is a platform that enables the deployment of production-ready, scalable ML systems with minimal engineering effort. It offers one-click deploys, real-time inference, and framework agnostic support. With PoplarML, users can seamlessly deploy ML models using a CLI tool to a fleet of GPUs and invoke their models through a REST API endpoint. The platform supports Tensorflow, Pytorch, and JAX models.
JFrog ML
JFrog ML is an AI platform designed to streamline AI development from prototype to production. It offers a unified MLOps platform to build, train, deploy, and manage AI workflows at scale. With features like Feature Store, LLMOps, and model monitoring, JFrog ML empowers AI teams to collaborate efficiently and optimize AI & ML models in production.
Blue Dot
Blue Dot is a leading AI tax compliance platform that offers solutions for global tax management and VAT recovery. The platform provides a comprehensive view of employee-driven transactions, ensuring tax compliance and reducing vulnerabilities. Blue Dot's technology leverages AI and ML to optimize VAT outcomes and automate the review process for taxable employee benefits. The platform is fully integrated with expense management systems, helping organizations streamline compliance efforts and improve data integrity.
Comet ML
Comet ML is an extensible, fully customizable machine learning platform that aims to move ML forward by supporting productivity, reproducibility, and collaboration. It integrates with existing infrastructure and tools to manage, visualize, and optimize models from training runs to production monitoring. Users can track and compare training runs, create a model registry, and monitor models in production all in one platform. Comet's platform can be run on any infrastructure, enabling users to reshape their ML workflow and bring their existing software and data stack.
Comet ML
Comet ML is a machine learning platform that integrates with your existing infrastructure and tools so you can manage, visualize, and optimize models—from training runs to production monitoring.
Comet ML
Comet ML is a machine learning platform that integrates with your existing infrastructure and tools so you can manage, visualize, and optimize models—from training runs to production monitoring.
UnfoldAI
UnfoldAI is a website offering articles, strategies, and tutorials for building production-grade ML systems. Authored by Simeon Emanuilov, the site covers topics such as deep learning, computer vision, LLMs, programming, MLOps, performance, scalability, and AI consulting. It aims to provide insights and best practices for professionals in the field of machine learning to create robust, efficient, and scalable systems.
Artsyl Technologies
Artsyl Technologies specializes in revolutionizing document processing through advanced AI-powered automation. Their flagship intelligent process automation platform, docAlpha, utilizes cutting-edge AI, RPA, and machine learning technologies to automate and optimize document workflows. By seamlessly integrating with organizations' ERP or Document Management Systems, docAlpha ensures enhanced efficiency, accuracy, and productivity across the entire business process.
PredictModel
PredictModel is an AI tool that specializes in creating custom Machine Learning models tailored to meet unique requirements. The platform offers a comprehensive three-step process, including generating synthetic data, training ML models, and deploying them to AWS. PredictModel helps businesses streamline processes, improve customer segmentation, enhance client interaction, and boost overall business performance. The tool maximizes accuracy through customized synthetic data generation and saves time and money by providing expert ML engineers. With a focus on automated lead prioritization, fraud detection, cost optimization, and planning, PredictModel aims to stay ahead of the curve in the ML industry.
FinetuneFast
FinetuneFast is an AI tool designed to help developers, indie makers, and businesses to efficiently finetune machine learning models, process data, and deploy AI solutions at lightning speed. With pre-configured training scripts, efficient data loading pipelines, and one-click model deployment, FinetuneFast streamlines the process of building and deploying AI models, saving users valuable time and effort. The tool is user-friendly, accessible for ML beginners, and offers lifetime updates for continuous improvement.
Salad
Salad is a distributed GPU cloud platform that offers fully managed and massively scalable services for AI applications. It provides the lowest priced AI transcription in the market, with features like image generation, voice AI, computer vision, data collection, and batch processing. Salad democratizes cloud computing by leveraging consumer GPUs to deliver cost-effective AI/ML inference at scale. The platform is trusted by hundreds of machine learning and data science teams for its affordability, scalability, and ease of deployment.
Rafay
Rafay is an AI-powered platform that accelerates cloud-native and AI/ML initiatives for enterprises. It provides automation for Kubernetes clusters, cloud cost optimization, and AI workbenches as a service. Rafay enables platform teams to focus on innovation by automating self-service cloud infrastructure workflows.
CloudEagle.ai
CloudEagle.ai is a modern SaaS procurement and management platform that offers AI/ML capabilities. It helps optimize SaaS stacks, manage contracts, streamline procurement workflows, and ensure cost savings by identifying unused licenses. The platform also assists in vendor research, renewal management, and automating provisioning processes. CloudEagle.ai is recognized for its AI/ML capabilities in the 2024 Gartner Magic Quadrant.
New Age Content Services LLP
New Age Content Services LLP is a specialized content and content marketing service provider for tech and emerging tech companies. With over a decade's experience, they offer services to power tech brands by providing messaging and marketing solutions. They focus on industries like IT, AI, ML, cognitive computing, data science/analytics, IoT, cybersecurity, and Web3. The company helps businesses maximize their content and marketing strategies through AI technology, aiming to improve digital marketing efficiency and personalize campaigns.
Derwen
Derwen is an open-source integration platform for production machine learning in enterprise, specializing in natural language processing, graph technologies, and decision support. It offers expertise in developing knowledge graph applications and domain-specific authoring. Derwen collaborates closely with Hugging Face and provides strong data privacy guarantees, low carbon footprint, and no cloud vendor involvement. The platform aims to empower AI engineers and domain experts with quality, time-to-value, and ownership since 2017.
20 - Open Source AI Tools
Detection-and-Classification-of-Alzheimers-Disease
This tool is designed to detect and classify Alzheimer's Disease using Deep Learning and Machine Learning algorithms on an early basis, which is further optimized using the Crow Search Algorithm (CSA). Alzheimer's is a fatal disease, and early detection is crucial for patients to predetermine their condition and prevent its progression. By analyzing MRI scanned images using Artificial Intelligence technology, this tool can classify patients who may or may not develop AD in the future. The CSA algorithm, combined with ML algorithms, has proven to be the most effective approach for this purpose.
awesome-mlops
Awesome MLOps is a curated list of tools related to Machine Learning Operations, covering areas such as AutoML, CI/CD for Machine Learning, Data Cataloging, Data Enrichment, Data Exploration, Data Management, Data Processing, Data Validation, Data Visualization, Drift Detection, Feature Engineering, Feature Store, Hyperparameter Tuning, Knowledge Sharing, Machine Learning Platforms, Model Fairness and Privacy, Model Interpretability, Model Lifecycle, Model Serving, Model Testing & Validation, Optimization Tools, Simplification Tools, Visual Analysis and Debugging, and Workflow Tools. The repository provides a comprehensive collection of tools and resources for individuals and teams working in the field of MLOps.
how-to-optim-algorithm-in-cuda
This repository documents how to optimize common algorithms based on CUDA. It includes subdirectories with code implementations for specific optimizations. The optimizations cover topics such as compiling PyTorch from source, NVIDIA's reduce optimization, OneFlow's elementwise template, fast atomic add for half data types, upsample nearest2d optimization in OneFlow, optimized indexing in PyTorch, OneFlow's softmax kernel, linear attention optimization, and more. The repository also includes learning resources related to deep learning frameworks, compilers, and optimization techniques.
optscale
OptScale is an open-source FinOps and MLOps platform that provides cloud cost optimization for all types of organizations and MLOps capabilities like experiment tracking, model versioning, ML leaderboards.
litdata
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.
cosdata
Cosdata is a cutting-edge AI data platform designed to power the next generation search pipelines. It features immutability, version control, and excels in semantic search, structured knowledge graphs, hybrid search capabilities, real-time search at scale, and ML pipeline integration. The platform is customizable, scalable, efficient, enterprise-grade, easy to use, and can manage multi-modal data. It offers high performance, indexing, low latency, and high requests per second. Cosdata is designed to meet the demands of modern search applications, empowering businesses to harness the full potential of their data.
recommenders
Recommenders is a project under the Linux Foundation of AI and Data that assists researchers, developers, and enthusiasts in prototyping, experimenting with, and bringing to production a range of classic and state-of-the-art recommendation systems. The repository contains examples and best practices for building recommendation systems, provided as Jupyter notebooks. It covers tasks such as preparing data, building models using various recommendation algorithms, evaluating algorithms, tuning hyperparameters, and operationalizing models in a production environment on Azure. The project provides utilities to support common tasks like loading datasets, evaluating model outputs, and splitting training/test data. It includes implementations of state-of-the-art algorithms for self-study and customization in applications.
clearml
ClearML is a suite of tools designed to streamline the machine learning workflow. It includes an experiment manager, MLOps/LLMOps, data management, and model serving capabilities. ClearML is open-source and offers a free tier hosting option. It supports various ML/DL frameworks and integrates with Jupyter Notebook and PyCharm. ClearML provides extensive logging capabilities, including source control info, execution environment, hyper-parameters, and experiment outputs. It also offers automation features, such as remote job execution and pipeline creation. ClearML is designed to be easy to integrate, requiring only two lines of code to add to existing scripts. It aims to improve collaboration, visibility, and data transparency within ML teams.
AiTreasureBox
AiTreasureBox is a versatile AI tool that provides a collection of pre-trained models and algorithms for various machine learning tasks. It simplifies the process of implementing AI solutions by offering ready-to-use components that can be easily integrated into projects. With AiTreasureBox, users can quickly prototype and deploy AI applications without the need for extensive knowledge in machine learning or deep learning. The tool covers a wide range of tasks such as image classification, text generation, sentiment analysis, object detection, and more. It is designed to be user-friendly and accessible to both beginners and experienced developers, making AI development more efficient and accessible to a wider audience.
katib
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.
ML-AI-2-LT
ML-AI-2-LT is a repository that serves as a glossary for machine learning and deep learning concepts. It contains translations and explanations of various terms related to artificial intelligence, including definitions and notes. Users can contribute by filling issues for unclear concepts or by submitting pull requests with suggestions or additions. The repository aims to provide a comprehensive resource for understanding key terminology in the field of AI and machine learning.
LLM4Opt
LLM4Opt is a collection of references and papers focusing on applying Large Language Models (LLMs) for diverse optimization tasks. The repository includes research papers, tutorials, workshops, competitions, and related collections related to LLMs in optimization. It covers a wide range of topics such as algorithm search, code generation, machine learning, science, industry, and more. The goal is to provide a comprehensive resource for researchers and practitioners interested in leveraging LLMs for optimization tasks.
awesome-ai4db-paper
The 'awesome-ai4db-paper' repository is a curated paper list focusing on AI for database (AI4DB) theory, frameworks, resources, and tools for data engineers. It includes a collection of research papers related to learning-based query optimization, training data set preparation, cardinality estimation, query-driven approaches, data-driven techniques, hybrid methods, pretraining models, plan hints, cost models, SQL embedding, join order optimization, query rewriting, end-to-end systems, text-to-SQL conversion, traditional database technologies, storage solutions, learning-based index design, and a learning-based configuration advisor. The repository aims to provide a comprehensive resource for individuals interested in AI applications in the field of database management.
Awesome_LLM_System-PaperList
Since the emergence of chatGPT in 2022, the acceleration of Large Language Model has become increasingly important. Here is a list of papers on LLMs inference and serving.
Awesome-LLM-Quantization
Awesome-LLM-Quantization is a curated list of resources related to quantization techniques for Large Language Models (LLMs). Quantization is a crucial step in deploying LLMs on resource-constrained devices, such as mobile phones or edge devices, by reducing the model's size and computational requirements.
awesome-cuda-tensorrt-fpga
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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.
Awesome-Efficient-AIGC
This repository, Awesome Efficient AIGC, collects efficient approaches for AI-generated content (AIGC) to cope with its huge demand for computing resources. It includes efficient Large Language Models (LLMs), Diffusion Models (DMs), and more. The repository is continuously improving and welcomes contributions of works like papers and repositories that are missed by the collection.
awesome-mobile-robotics
The 'awesome-mobile-robotics' repository is a curated list of important content related to Mobile Robotics and AI. It includes resources such as courses, books, datasets, software and libraries, podcasts, conferences, journals, companies and jobs, laboratories and research groups, and miscellaneous resources. The repository covers a wide range of topics in the field of Mobile Robotics and AI, providing valuable information for enthusiasts, researchers, and professionals in the domain.
llm-twin-course
The LLM Twin Course is a free, end-to-end framework for building production-ready LLM systems. It teaches you how to design, train, and deploy a production-ready LLM twin of yourself powered by LLMs, vector DBs, and LLMOps good practices. The course is split into 11 hands-on written lessons and the open-source code you can access on GitHub. You can read everything and try out the code at your own pace.
20 - OpenAI Gpts
Code Solver
ML/DL expert focused on mathematical modeling, Kaggle competitions, and advanced ML models.
ML Engineer GPT
I'm a Python and PyTorch expert with knowledge of ML infrastructure requirements ready to help you build and scale your ML projects.
Data Analysis and Operations Research Expert
Expert in ML, operations research, Treasure Data, Mac M2
CV & Resume ATS Optimize + 🔴Match-JOB🔴
Professional Resume & CV Assistant 📝 Optimize for ATS 🤖 Tailor to Job Descriptions 🎯 Compelling Content ✨ Interview Tips 💡
Website Conversion by B12
I'll help you optimize your website for more conversions, and compare your site's CRO potential to competitors’.
Thermodynamics Advisor
Advises on thermodynamics processes to optimize system efficiency.
Cloud Architecture Advisor
Guides cloud strategy and architecture to optimize business operations.
International Tax Advisor
Advises on international tax matters to optimize company's global tax position.
Investment Management Advisor
Provides strategic financial guidance for investment behavior to optimize organization's wealth.
ESG Strategy Navigator 🌱🧭
Optimize your business with sustainable practices! ESG Strategy Navigator helps integrate Environmental, Social, Governance (ESG) factors into corporate strategy, ensuring compliance, ethical impact, and value creation. 🌟