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Founded by passionate advocates of learning and innovation, Learni set out to make professional training accessible to everyone, everywhere in the world. Our team works in the largest cities such as Paris, Lyon, Marseille, and internationally, to support talents and organizations in their skills development.
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The Training: Mastering ONNX - Deploy and Interoperate Your AI Models on All Platforms training is delivered in-person or remotely (blended-learning, e-learning, virtual classroom, remote in-person). At Learni, a Qualiopi-certified training organization, each program is designed to maximize skills acquisition, regardless of the training mode chosen.
The trainer alternates between demonstrative, interrogative, and active methods (through practical exercises and/or real-world scenarios). This pedagogical approach ensures concrete and directly applicable learning in the workplace.
To ensure the quality of the Training: Mastering ONNX - Deploy and Interoperate Your AI Models on All Platforms training, Learni provides the following teaching resources:
For in-house training at a location external to Learni, the client ensures and commits to having all necessary teaching materials (IT equipment, internet connection...) for the proper conduct of the training action in accordance with the prerequisites indicated in the communicated training program.
The assessment of skills acquired during the Training: Mastering ONNX - Deploy and Interoperate Your AI Models on All Platforms training is carried out through:
Learni is committed to the accessibility of its professional training programs. All our training programs are accessible to people with disabilities. Our teams are available to adapt teaching methods to your specific needs. Do not hesitate to contact us for any accommodation request.
Learni training programs are available for inter-company and intra-company settings, both in-person and remote. Registration is possible up to 48 business hours before the start of training. Our programs are eligible for OPCO, Pôle emploi, and FNE-Formation funding. Contact us to discuss your training project and funding possibilities.
History and architecture of ONNX. Model representation standards. Overview of compatible frameworks (PyTorch, TensorFlow, Scikit-learn, Keras, etc.). Concrete examples of model exchange and business benefits. Use of ONNX import/export tools.
Advanced model conversion techniques: operator management, limitations, and solutions. Practical cases of complex conversions (GAN networks, NLP, CNN). Introduction to ONNX Opset. Model optimization and quantization to accelerate inference. ONNX model diagnostic and validation tools (Netron, ONNX Checker).
ONNX model deployment in production: servers, edge, cloud (Azure, AWS, GCP). Accelerate inferences with ONNX Runtime on CPU/GPU/Jetson. Performance benchmarking. Implementation of automated pipelines (CI/CD for AI). Best practices for maintaining interoperable models, version management, and future compatibility.
Target audience
Data scientists, AI developers, machine learning engineers, and AI professionals seeking to optimize model interoperability across different frameworks.
Prerequisites
Basics in machine learning, knowledge of at least one Deep Learning framework (TensorFlow, PyTorch, Scikit-learn, etc.).
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