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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 Keras: Mastering Deep Learning with Python and TensorFlow 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 Keras: Mastering Deep Learning with Python and TensorFlow 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 Keras: Mastering Deep Learning with Python and TensorFlow 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.
Overview of deep learning; neural network architectures; introduction to Keras, installation, project structure; exploration of basic layers (Dense, Activation); first training on a simple dataset (MNIST).
Convolutional networks (CNN) for image processing; recurrent networks (RNN, LSTM) for sequences; handling overfitting issues (Dropout, EarlyStopping); hyperparameter tuning (optimizers, learning rate scheduler); training monitoring with TensorBoard.
Data augmentation strategies; integration of data pipelines with tf.data; saving and exporting models (SavedModel, HDF5); deployment on REST API with Flask/FastAPI; concrete cases and hands-on practice with real datasets.
Target audience
Developers, data scientists, engineers wishing to specialize in deep learning with Keras
Prerequisites
Advanced Python skills and basics in mathematics for artificial intelligence
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