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Explore low-cost, energy-efficient sensor data acquisition at scale with tinyML. Learn from Everynet's CTO about hardware and software optimizations, use cases, and best practices.
Explore tinyML's compact guide on using neural networks for Diabetic Retinopathy screening. Learn about CNNs, data processing, model training, and energy-efficient implementations.
Join tinyML's South African meetup for an introduction to tinyML, its applications, and tools. Engage in Q&A and provide feedback for future events. Less than 1-hour commitment.
Explore the Neuromorphic Analog Signal Processor (NASP) concept with tinyML. Learn about neuromorphic computing, neural networks, and the transformative NASP technology in just 1-2 hours.
Explore the RISC-V ISA specifications, software support, and opportunities for open-source contributions in low-power ML applications with tinyML. 1-2 hours workload.
Explore AI and deep neural networks with tinyML's under 1-hour material. Learn about Maxim's technology for power-efficient AI at the IoT edge.
Explore AI/ML solutions for low-power Edge platforms with tinyML. Learn about challenges, opportunities, and practical applications in less than an hour.
Learn to build products using Edge AI/TinyML on MCUs with tinyML. Understand sensor optimization, component specification, and data collection cost minimization in under 1 hour.
Learn to run speech recognition models on low-power devices with Fluent.ai's Vikrant Tomar & Sam Myer in this less than 1-hour tinyML webcast.
Explore efficient multi-resolution visual computing on mobile systems with tinyML. Learn to optimize image resolution for energy saving and meet computational needs with minimal developer burden.
Explore the Akida Neural Processor's low-power, high-performance SoC for edge applications in this less than 1-hour webcast by tinyML. Learn about its unique architecture, on-chip learning, and more.
Explore software-defined imaging and adaptive video subsampling for energy-efficient object tracking with tinyML. Learn from Arizona State University's Suren Jayasuriya in under an hour.
Explore the use of Kronecker Products for compressing sequence-based neural networks in this less than 1-hour webcast by tinyML. Learn about achieving 15-38x compression factors and recovering accuracy in NLP tasks.
Learn to apply tinyML in battery-powered anomaly sensors for predictive maintenance of industrial assets with tinyML. Less than 1-hour workload.
Learn to train neural networks for sensor data in under an hour with tinyML. Understand data collection, project investigation, and achieving neural network performance for gestures.
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