Entrevista a Cristina Díaz
summary
Recommends beginning ML/AI with Google Cloud workshops for hands‑on basics or with TensorFlow as the common entry path; says concrete learning comes from small guided labs that reinforce concepts. Claims cloud hosting lets teams pay only for needed capacity, avoid buying hardware, and rely on providers to provision instances and handle managed load balancing and auto‑scaling so deployments scale automatically without manual infrastructure setup.
AI-written summary · about
related talks
27mKeynote - Google Cloud, Machine Learning
51mCloud AI: How to Get Started Injecting AI Into Your Applications
40mCloud-based Machine Learning Offerings - Beginner's Perspective
32mMachine Learning with Google Cloud Platform
31mProductionizing ML with ML Ops and Cloud AI
33mAI with a DevOps mindset - experimentation, sharing ..
35mDoing Data Science on Cloud
59mMachine Intelligence at Google Scale
