how to train custom AI models without coding
AI Search Visibility Analysis
Analyze how brands appear across multiple AI search platforms for a specific prompt
Total Mentions
Total number of times a brand appears
across all AI platforms for this prompt
Platform Presence
Number of AI platforms where the brand
was mentioned for this prompt
Linkbacks
Number of times brand website was
linked in AI responses
Sentiment
Overall emotional tone when brand is
mentioned (Positive/Neutral/Negative)
Brand Performance Across AI Platforms
| BRAND | TOTAL MENTIONS | PLATFORM PRESENCE | LINKBACKS | SENTIMENT | SCORE |
|---|---|---|---|---|---|
1Amazon SageMaker Canvas | 0 | 0 | 95 | ||
2Azure AutoML | 0 | 0 | 95 | ||
3DataRobot | 0 | 0 | 95 | ||
4Google AutoML | 0 | 0 | 95 | ||
5Google Teachable Machine | 0 | 0 | 95 | ||
6Microsoft Lobe | 0 | 0 | 95 | ||
7Runway ML | 0 | 0 | 95 | ||
8Bubble | 0 | 0 | 55 | ||
9Airtable | 0 | 0 | 55 |
Strategic Insights & Recommendations
Dominant Brand
Google Teachable Machine and Microsoft Lobe emerge as the most accessible entry points for beginners, while Amazon SageMaker Canvas and DataRobot dominate enterprise solutions.
Platform Gap
ChatGPT focuses on specific platform recommendations while Perplexity provides a comprehensive methodology and comparison framework for choosing approaches.
Link Opportunity
Both platforms could benefit from linking to official documentation and tutorials for the mentioned no-code AI platforms to provide users with direct access to getting started.
Key Takeaways for This Prompt
No-code AI platforms like Google Teachable Machine and Microsoft Lobe make machine learning accessible to non-programmers through drag-and-drop interfaces.
Data quality is the most critical factor for successful AI model training, regardless of the platform used.
AutoML platforms offer a middle ground between no-code simplicity and full coding control for more complex projects.
Enterprise solutions like Amazon SageMaker Canvas and DataRobot provide scalable options for business-grade AI model development.
AI Search Engine Responses
Compare how different AI search engines respond to this query
ChatGPT
BRAND (5)
SUMMARY
ChatGPT provides a comprehensive overview of no-code AI platforms, highlighting five key tools: Google Teachable Machine for quick prototypes, Microsoft Lobe for image classification, Amazon SageMaker Canvas for various model types, Runway ML for creative professionals, and DataRobot AI Cloud for enterprise solutions. The response emphasizes how these platforms democratize AI development through intuitive drag-and-drop interfaces, making machine learning accessible to users without programming expertise.
REFERENCES (4)
Perplexity
BRAND (4)
SUMMARY
Perplexity offers a detailed step-by-step guide for training custom AI models without coding, covering the entire process from problem definition to deployment. It compares no-code, AutoML, and coding approaches in a helpful table format, emphasizing data quality as the critical success factor. The response provides practical considerations including cost, transparency, and customization trade-offs, making it valuable for users choosing between different approaches.
Google AIO
SUMMARY
No summary available.
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