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☁️ Machine Learning desde Google Cloud y Mitigando alucinaciones con Neo4j
Explore the intersection of machine learning, Google Cloud, and Neo4j, with insights on mitigating hallucinations, industry trends, and community engagement, and discover how the Google Cloud community is driving innovation and growth.
- Machine Learning: Google Cloud provides a wide range of machine learning tools and services, including AutoML, Transcoder, and others.
- Neo4j: A graph database that allows for efficient querying and storage of relationships between data entities.
- Mitigating hallucinations: Techniques for reducing the impact of hallucinations in machine learning models, such as using external validation datasets and ensembling.
- Industry trends: Discussion of current industry trends and challenges in machine learning, including the need for explainability and transparency.
- Community engagement: Invitation to participate in the Google Cloud community and contribute to the development of machine learning models and services.
- Code of conduct: Guidelines for respectful and professional behavior in the community, including no tolerance for racism, sexism, or other forms of discrimination.
- Georgia is here: The community is global and inclusive, with participants from diverse backgrounds and industries.
- Company testimonials: Positive experiences from companies that have used Google Cloud services to drive innovation and growth, such as Making Science.
- Ongoing development: The Google Cloud community is constantly evolving and improving, with new tools and services being developed to meet emerging needs and challenges.