Best AI tools for< Backend Ml Engineer >
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20 - AI tool Sites
Chai AI
Chai AI is an AI application developed by CHAI RESEARCH CORP. It is a platform that offers generative AI solutions and tools for various tasks. The application is designed to provide users with advanced AI capabilities for tasks such as chatbot development, reward models, rejection sampling, blending, reinforcement learning, and more. Chai AI aims to enhance user engagement and provide innovative solutions through AI technology.
Auto Backend
Auto Backend is a web application that allows users to easily set up and describe their backend services. Users can define the functionality they want their backend to perform in just a few sentences. The application offers features like creating a Todo List, checking Reddit Trending topics, getting Random Pokemon information, simulating a Twitter Clone, managing a Calendar Backend, and checking Ethereum Balance. Users can submit their backend description within a limit of 250 characters.
Goptimise
Goptimise is a no-code AI-powered scalable backend builder that helps developers craft scalable, seamless, powerful, and intuitive backend solutions. It offers a solid foundation with robust and scalable infrastructure, including dedicated infrastructure, security, and scalability. Goptimise simplifies software rollouts with one-click deployment, automating the process and amplifying productivity. It also provides smart API suggestions, leveraging AI algorithms to offer intelligent recommendations for API design and accelerating development with automated recommendations tailored to each project. Goptimise's intuitive visual interface and effortless integration make it easy to use, and its customizable workspaces allow for dynamic data management and a personalized development experience.
Convex
Convex is a fullstack TypeScript development platform that serves as an open-source backend for application builders. It offers a comprehensive set of APIs and tools to build, launch, and scale applications efficiently. With features like real-time collaboration, optimized transactions, and over 80 OAuth integrations, Convex simplifies backend operations and allows developers to focus on delivering value to customers. The platform enables developers to write backend logic in TypeScript, perform database operations with strong consistency, and integrate with various third-party services seamlessly. Convex is praised for its reliability, simplicity, and developer experience, making it a popular choice for modern software development projects.
Rowy
Rowy is a low-code backend platform that allows users to manage their database on a spreadsheet-like interface and build powerful backend cloud functions without leaving their browser. It offers a variety of features such as derivative fields, action fields, extensions, webhooks, and integrations with popular tools like Google Vision, GPT-3, Figma, and Webflow. Rowy is designed to be accessible to both developers and non-technical users, making it a versatile tool for building and managing backend applications.
Backmesh
Backmesh is an AI tool that serves as a proxy on edge CDN servers, enabling secure and direct access to LLM APIs without the need for a backend or SDK. It allows users to call LLM APIs from their apps, ensuring protection through JWT verification and rate limits. Backmesh also offers user analytics for LLM API calls, helping identify usage patterns and enhance user satisfaction within AI applications.
Works
Works is a platform that connects enterprises with the top 1% of remote tech talent. It uses advanced AI technology to ensure precision-matching of talent to project requirements, saving time and resources. Works offers transparent pricing with a flat 10% transaction fee and provides risk-free hiring with payment only when the work is completed to satisfaction.
Volamail
Volamail is an AI-powered email platform that simplifies the email writing process for everyone. It offers AI-assisted editing to help users compose email templates effortlessly. The platform supports importing existing emails in plain HTML format and allows self-hosting for easy deployment. With Volamail, users can send transactional emails via a simple HTTP call without the need for dependencies. The platform is constantly evolving with new features like AI template generation, inline AI editing, and custom domains. Volamail provides simple and scalable pricing options, including a free plan for small projects and affordable custom plans for larger teams.
BuildShip
BuildShip is a low-code visual backend builder that allows users to create powerful APIs in minutes. It is powered by AI and offers a variety of features such as pre-built nodes, multimodal flows, and integration with popular AI models. BuildShip is suitable for a wide range of users, from beginners to experienced developers. It is also a great tool for teams who want to collaborate on backend development projects.
Amplication
Amplication is an AI-powered platform for .NET and Node.js app development, offering the world's fastest way to build backend services. It empowers developers by providing customizable, production-ready backend services without vendor lock-ins. Users can define data models, extend and customize with plugins, generate boilerplate code, and modify the generated code freely. The platform supports role-based access control, microservices architecture, continuous Git sync, and automated deployment. Amplication is SOC-2 certified, ensuring data security and compliance.
Privado AI
Privado AI is a privacy engineering tool that bridges the gap between privacy compliance and software development. It automates personal data visibility and privacy governance, helping organizations to identify privacy risks, track data flows, and ensure compliance with regulations such as CPRA, MHMDA, FTC, and GDPR. The tool provides real-time visibility into how personal data is collected, used, shared, and stored by scanning the code of websites, user-facing applications, and backend systems. Privado offers features like Privacy Code Scanning, programmatic privacy governance, automated GDPR RoPA reports, risk identification without assessments, and developer-friendly privacy guidance.
DocDriven
DocDriven is an AI-powered documentation-driven API development tool that provides a shared workspace for optimizing the API development process. It helps in designing APIs faster and more efficiently, collaborating on API changes in real-time, exploring all APIs in one workspace, generating AI code, maintaining API documentation, and much more. DocDriven aims to streamline communication and coordination among backend developers, frontend developers, UI designers, and product managers, ensuring high-quality API design and development.
Koxy AI
Koxy AI is an AI-powered serverless back-end platform that allows users to build globally distributed, fast, secure, and scalable back-ends with no code required. It offers features such as live logs, smart errors handling, integration with over 80,000 AI models, and more. Koxy AI is designed to help users focus on building the best service possible without wasting time on security and latency concerns. It provides a No-SQL JSON-based database, real-time data synchronization, cloud functions, and a drag-and-drop builder for API flows.
micro1
micro1 is an AI recruitment engine that helps companies hire deeply vetted engineers quickly and efficiently. The platform uses AI technology to screen thousands of candidates, certify the top 1%, and match them with companies looking to hire engineering talent. micro1 handles international employment laws, benefits, and global payroll, making the hiring process seamless for businesses. With a focus on global compliance and cost-effectiveness, micro1 aims to revolutionize the way companies recruit top engineering talent.
Treblle
Treblle is an End to End APIOps Platform that helps engineering and product teams build, ship, and understand their REST APIs in one single place. It offers features such as API Observability, API Documentation, API Governance, API Security, and API Analytics. With a focus on empowering API producers and consumers, Treblle provides actionable data in real-time, customizable dashboards, and automated API development. The platform aims to improve API release times, enhance developer experience, and ensure API quality and security.
AgentLabs
AgentLabs is a frontend-as-a-service platform that allows developers to build and share AI-powered chat-based applications in minutes, without any front-end experience. It provides a range of features such as real-time and asynchronous communication, background task management, backend agnosticism, and support for Markdown, files, and more.
Software Engineer Interview Questions Generator
The Software Engineer Interview Questions Generator is an AI tool designed to help software engineers prepare for interviews by generating a wide range of technical questions related to various programming languages, frameworks, databases, and cloud services. Users can select specific topics and the number of questions they want to generate, making it a valuable resource for interview preparation. The tool leverages AI technology to provide relevant and challenging questions that cover a broad spectrum of software engineering topics.
YouTeam
YouTeam is an AI-powered platform that offers a transparent vetting process for hiring engineers. Leveraging deep learning technology, YouTeam provides customized vetting criteria tailored to each role's responsibilities and required skillset. The platform streamlines the hiring process by presenting engineering candidates aligned with the company's unique standards, allowing for a final interview to select the perfect match. With features like technical skill review assessments, coding assessments, and soft skills & culture fit questions, YouTeam ensures a data-rich candidate profile for informed decision-making.
Engine
Engine is an AI tool that allows users to build an app with just words, eliminating the need for coding or infrastructure setup. Users can create a managed LibSQL database and Typescript API using natural language commands. The platform offers industry-standard authentication and instant backend deployment. Engine enables users to watch real-time updates of their database schema and API on GitHub, and deploy their complete Typescript API with a single click.
React Native Starter AI
React Native Starter AI is an all-in-one development kit designed to help users quickly launch their mobile apps with AI functionality. The boilerplate template includes integrations such as AI tools, Firebase functions, analytics, authentication, in-app purchases, and more. It aims to save developers time by providing pre-built components and screens for building AI mobile applications. With React Native Starter AI, users can easily customize and publish their apps on mobile app stores, catering to both beginner and experienced developers.
20 - Open Source Tools
ml-road-map
The Machine Learning Road Map is a comprehensive guide designed to take individuals from various levels of machine learning knowledge to a basic understanding of machine learning principles using high-quality, free resources. It aims to simplify the complex and rapidly growing field of machine learning by providing a structured roadmap for learning. The guide emphasizes the importance of understanding AI for everyone, the need for patience in learning machine learning due to its complexity, and the value of learning from experts in the field. It covers five different paths to learning about machine learning, catering to consumers, aspiring AI researchers, ML engineers, developers interested in building ML applications, and companies looking to implement AI solutions.
repromodel
ReproModel is an open-source toolbox designed to boost AI research efficiency by enabling researchers to reproduce, compare, train, and test AI models faster. It provides standardized models, dataloaders, and processing procedures, allowing researchers to focus on new datasets and model development. With a no-code solution, users can access benchmark and SOTA models and datasets, utilize training visualizations, extract code for publication, and leverage an LLM-powered automated methodology description writer. The toolbox helps researchers modularize development, compare pipeline performance reproducibly, and reduce time for model development, computation, and writing. Future versions aim to facilitate building upon state-of-the-art research by loading previously published study IDs with verified code, experiments, and results stored in the system.
awesome-transformer-nlp
This repository contains a hand-curated list of great machine (deep) learning resources for Natural Language Processing (NLP) with a focus on Generative Pre-trained Transformer (GPT), Bidirectional Encoder Representations from Transformers (BERT), attention mechanism, Transformer architectures/networks, Chatbot, and transfer learning in NLP.
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.
clearml-server
ClearML Server is a backend service infrastructure for ClearML, facilitating collaboration and experiment management. It includes a web app, RESTful API, and file server for storing images and models. Users can deploy ClearML Server using Docker, AWS EC2 AMI, or Kubernetes. The system design supports single IP or sub-domain configurations with specific open ports. ClearML-Agent Services container allows launching long-lasting jobs and various use cases like auto-scaler service, controllers, optimizer, and applications. Advanced functionality includes web login authentication and non-responsive experiments watchdog. Upgrading ClearML Server involves stopping containers, backing up data, downloading the latest docker-compose.yml file, configuring ClearML-Agent Services, and spinning up docker containers. Community support is available through ClearML FAQ, Stack Overflow, GitHub issues, and email contact.
SuperKnowa
SuperKnowa is a fast framework to build Enterprise RAG (Retriever Augmented Generation) Pipelines at Scale, powered by watsonx. It accelerates Enterprise Generative AI applications to get prod-ready solutions quickly on private data. The framework provides pluggable components for tackling various Generative AI use cases using Large Language Models (LLMs), allowing users to assemble building blocks to address challenges in AI-driven text generation. SuperKnowa is battle-tested from 1M to 200M private knowledge base & scaled to billions of retriever tokens.
backend.ai
Backend.AI is a streamlined, container-based computing cluster platform that hosts popular computing/ML frameworks and diverse programming languages, with pluggable heterogeneous accelerator support including CUDA GPU, ROCm GPU, TPU, IPU and other NPUs. It allocates and isolates the underlying computing resources for multi-tenant computation sessions on-demand or in batches with customizable job schedulers with its own orchestrator. All its functions are exposed as REST/GraphQL/WebSocket APIs.
crazyai-ml
The 'crazyai-ml' repository is a collection of resources related to machine learning, specifically focusing on explaining artificial intelligence models. It includes articles, code snippets, and tutorials covering various machine learning algorithms, data analysis, model training, and deployment. The content aims to provide a comprehensive guide for beginners in the field of AI, offering practical implementations and insights into popular machine learning packages and model tuning techniques. The repository also addresses the integration of AI models and frontend-backend concepts, making it a valuable resource for individuals interested in AI applications.
mosec
Mosec is a high-performance and flexible model serving framework for building ML model-enabled backend and microservices. It bridges the gap between any machine learning models you just trained and the efficient online service API. * **Highly performant** : web layer and task coordination built with Rust 🦀, which offers blazing speed in addition to efficient CPU utilization powered by async I/O * **Ease of use** : user interface purely in Python 🐍, by which users can serve their models in an ML framework-agnostic manner using the same code as they do for offline testing * **Dynamic batching** : aggregate requests from different users for batched inference and distribute results back * **Pipelined stages** : spawn multiple processes for pipelined stages to handle CPU/GPU/IO mixed workloads * **Cloud friendly** : designed to run in the cloud, with the model warmup, graceful shutdown, and Prometheus monitoring metrics, easily managed by Kubernetes or any container orchestration systems * **Do one thing well** : focus on the online serving part, users can pay attention to the model optimization and business logic
kafka-ml
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.
ML-Bench
ML-Bench is a tool designed to evaluate large language models and agents for machine learning tasks on repository-level code. It provides functionalities for data preparation, environment setup, usage, API calling, open source model fine-tuning, and inference. Users can clone the repository, load datasets, run ML-LLM-Bench, prepare data, fine-tune models, and perform inference tasks. The tool aims to facilitate the evaluation of language models and agents in the context of machine learning tasks on code repositories.
chronon
Chronon is a platform that simplifies and improves ML workflows by providing a central place to define features, ensuring point-in-time correctness for backfills, simplifying orchestration for batch and streaming pipelines, offering easy endpoints for feature fetching, and guaranteeing and measuring consistency. It offers benefits over other approaches by enabling the use of a broad set of data for training, handling large aggregations and other computationally intensive transformations, and abstracting away the infrastructure complexity of data plumbing.
free-for-life
A massive list including a huge amount of products and services that are completely free! ⭐ Star on GitHub • 🤝 Contribute # Table of Contents * APIs, Data & ML * Artificial Intelligence * BaaS * Code Editors * Code Generation * DNS * Databases * Design & UI * Domains * Email * Font * For Students * Forms * Linux Distributions * Messaging & Streaming * PaaS * Payments & Billing * SSL
venice
Venice is a derived data storage platform, providing the following characteristics: 1. High throughput asynchronous ingestion from batch and streaming sources (e.g. Hadoop and Samza). 2. Low latency online reads via remote queries or in-process caching. 3. Active-active replication between regions with CRDT-based conflict resolution. 4. Multi-cluster support within each region with operator-driven cluster assignment. 5. Multi-tenancy, horizontal scalability and elasticity within each cluster. The above makes Venice particularly suitable as the stateful component backing a Feature Store, such as Feathr. AI applications feed the output of their ML training jobs into Venice and then query the data for use during online inference workloads.
ivy
Ivy is an open-source machine learning framework that enables you to: * 🔄 **Convert code into any framework** : Use and build on top of any model, library, or device by converting any code from one framework to another using `ivy.transpile`. * ⚒️ **Write framework-agnostic code** : Write your code once in `ivy` and then choose the most appropriate ML framework as the backend to leverage all the benefits and tools. Join our growing community 🌍 to connect with people using Ivy. **Let's** unify.ai **together 🦾**
ludwig
Ludwig is a declarative deep learning framework designed for scale and efficiency. It is a low-code framework that allows users to build custom AI models like LLMs and other deep neural networks with ease. Ludwig offers features such as optimized scale and efficiency, expert level control, modularity, and extensibility. It is engineered for production with prebuilt Docker containers, support for running with Ray on Kubernetes, and the ability to export models to Torchscript and Triton. Ludwig is hosted by the Linux Foundation AI & Data.
ai-on-gke
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
ivy
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.
onnxruntime-server
ONNX Runtime Server is a server that provides TCP and HTTP/HTTPS REST APIs for ONNX inference. It aims to offer simple, high-performance ML inference and a good developer experience. Users can provide inference APIs for ONNX models without writing additional code by placing the models in the directory structure. Each session can choose between CPU or CUDA, analyze input/output, and provide Swagger API documentation for easy testing. Ready-to-run Docker images are available, making it convenient to deploy the server.
20 - OpenAI Gpts
[サンプル] InterviewCat Backend Questions
問題集からバックエンドの技術質問(57+問)をランダムで出題します。回答に対して点数、評価ポイント、改善点を出し、最終的に面接に合格したかどうかを判断します。こちらはサンプルバージョンです。掲載問題数は減らしています。
Principal Backend Engineer
Expert Backend Developer: Skilled in Python, Java, Node.js, Ruby, PHP for robust backend solutions.
C# Expert
Hello, I'm your C# Backend Expert! Ready to solve all your C# and .Net Core queries.
FAANG Interviewer
I simulate software engineering interviews using FAANG Technical Questions and provide feedback.
[latest] FastAPI GPT
Up-to-date FastAPI coding assistant with knowledge of the latest version. Part of the [latest] GPTs family.
Elixir Code Assistant
This bot helps refine elixir code, especially genservers, and liveviews
Supabase Sensei
Supabase expert also supports query generation and Flutter code generation
MochaJS Expert in JavaScript unit testing
Assistant polyglotte pour tests unitaires avec MochaJS
JAVA开发工程师
精通所有java知识和框架,特别是springboot和springcloud后台接口开发以及实体类和mysql完整流程crud完整代码开发。解决一切java报错问题,具备JAVA资深工程师能力