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The ML category is a broad collection of 674 tools that apply machine learning across industries and functions, from healthcare documentation and legal research to user research, code generation, and content creation. It captures AI applications that do not fit cleanly into a single vertical.

Hugging Face

general

Open-source hub for ML models, datasets, and inference.

From $0.6 61 · 48,059 votes

Typing Mind

general

Frontend for ChatGPT, Claude, Gemini, and other LLMs with low costs

Paid 39 · 10,065 votes

AI.LS

general

ChatGPT interface supporting GPT-3.5, GPT-4, and Claude with free credits

Paid 38 · 49,737 votes

Interview Solver

general

Real-time LeetCode solutions for live coding interviews

Paid 38 · 60,481 votes

Dicte.ai

general

Meeting transcription and note-taking with AI insights

Paid 37 · 54,398 votes

Miraa

general

Learn languages through media with AI translation

Paid 37 · 48,133 votes

Echo Voice AI

general

Clone voices from short audio samples

Paid 37 · 46,580 votes

Video-GPT

general

Ask questions about video content

Paid 37 · 36,346 votes

Conversease

general

Home floor plan design with drag-and-drop editor and 3D view

Paid 36 · 28,437 votes

Life Story AI

general

Preserve family stories as a printed book

Paid 36 · 27,836 votes

StockGPT

general

Ask questions about Tesla stock and company information

Paid 35 · 14,020 votes

Essay Grader AI

general

Grade essays in minutes using AI rubrics

Paid 33 · 5,492 votes

GrammarBot App

general

Open-source API for grammar and spell checking in multiple languages

Paid 32 · 2,804 votes

GETitOUT

general

Generate buyer personas and convert features into benefits

Paid 31 · 2,215 votes

Long Summary

general

Summarize text, articles, PDFs, and videos in 50+ languages

Paid 31 · 2,088 votes

Because this category covers so many domains, browsing by sub-use case is more efficient than scrolling the full list. Tools like Hippo Scribe and SopCreator serve very specific professional workflows, while others like User Evaluation or Userpersona target product and UX teams. The quality bar across the category is uneven: some tools are mature products with enterprise customers, while others are early-stage experiments. When evaluating any tool in this space, look for evidence of actual accuracy and reliability in your specific domain, since ML performance varies dramatically across tasks. Integration depth and data handling are often the deciding factors for business use. Pricing models are diverse, from usage-based API billing to flat-rate SaaS subscriptions. Open-source alternatives exist for many of the underlying tasks, so for teams with technical resources, comparing commercial tools against self-hosted options is worth the effort.