Hands-on Deep Learning and Visual Recognition with Keras/Tensorflow

Home Forums Data Science Camp Hands-on Deep Learning and Visual Recognition with Keras/Tensorflow

This topic contains 1 reply, has 2 voices, and was last updated by  mahtoji@gmail.com 1 year, 1 month ago.

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  • #728 Score: 0

    In this hands-on session we’ll work with several datasets, such as MNIST handwritten digit dataset, Traffic Sign dataset, and build progressively more complex models to recognize images.

    (1) We’ll use classifiers from Scikit-Learn;

    (2) Implement LeNet-5 convolutional neural network in Keras/Tensorflow.

    (3) Use transfer learning technique based on Inception or ResNet architectures in Keras/Tensforflow.

    We will analyze and compare performance of each model and dataset combination, and discuss various issues related to data preparation and training.

    This is a hands-on session, so bring your laptop, or use your instance at AWS for the duration of the session. I will publish a docker image with all libraries and datasets shortly, to simplify the setup.

     

    BIO:

    Alex Kalinin, VP Product and Data Science @ home.ai

    https://www.linkedin.com/in/alexkalinin/

    #791 Score: 0

    mahtoji@gmail.com
    Participant

    Hi I am looking for the slides & video for this talk. I enjoyed attending this talk.

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