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Cisco Learning Credits

Cisco Learning Credits (CLCs) zijn prepaid trainingsvouchers die rechtstreeks bij Cisco worden ingewisseld en die het plannen van uw succes eenvoudiger maken bij de aankoop van Cisco-producten en -services.

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Het Fortinet Network Security Expert (NSE) -programma is een training- en certificeringsprogramma op acht niveaus om ingenieurs van hun netwerkbeveiliging te leren voor Fortinet FW-vaardigheden en -ervaring.

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    Beginning Application Development with TensorFlow and Keras

    Enroll Now
    Duration
    2 Dagen
    Delivery
    (Online and onsite)
    Price
    Price Upon Request
    The Beginning Application Development with TensorFlow and Keras course covers the development of a real-world application powered by TensorFlow and Keras. TensorFlow is popular software created by Google (and open source contributors) to facilitate the development of machine learning applications, particularly those that use deep learning. Keras is an interface that facilitates the development of deep learning models. The course starts with a hands-on introduction to TensorFlow and Keras. Then we move to the architecture of an example model, selecting the right layers to solve an example problem (predicting Bitcoin prices). Then we move on to the training and evaluation of the model. We will finish by deploying the model as a real-world product: a web-application (with an HTTP API) that uses Flask to make our model predictions available to the world.  

    This is a 2-day course packaged with the right balance of theory and hands-on activities that will help you easily learn TensorFlow and Keras from scratch.

    This course will provide you with a blueprint of how to build an application that generates predictions using a deep learning model. From there you can continue to improve the example model”either by adding more data, computing more features, or changing its architecture”continuously increasing its prediction accuracy, or create a completely new model, changing the core components of the application as you see fit.

    Lesson 1: Introduction to Neural Networks and Deep Learning

    • What are Neural Networks?
    • Configuring a Deep Learning Environment

    Lesson 2: Model Architecture

    • Choosing the Right Model Architecture
    • Using Keras as a TensorFlow Interface

    Lesson 3: Model Evaluation and Evaluation

    • Model Evaluation
    • Hyperparameter Optimization

    Lesson 4: Productization

    • Handling New Data
    • Deploying a Model as a Web Application

    This course is designed for developers, analysts, and data scientists interested in developing applications using TensorFlow and Keras.

    Hardware:
    For successful completion of this course, students will require computer systems with the following:

    • Processor: 2.6 GHz or higher, preferably multi-core
    • Memory: 4 GB RAM
    • Hard disk: 10 GB
    • Projector
    • Internet connection

     

    Software:

    • Operating System: Windows (8 or higher).
    • Visual Studio Code:https://code.visualstudio.com
    • Python 3: Follow instructions on the website: https://www.python.org/downloads/
    • TensorFlow 1.4 or higher on Windows: Follow instructions in website: https://www.tensorflow.org/install/install_windows
    • Keras 2: Follow instructions on the website (Keras only): https://keras.io/#installation

     

    Installation and Setup

    • Download and install Visual Studio Code from this website: https://code.visualstudio.com/
    • Download and install Python 3 from this website: https://www.python.org/downloads/
    • Download and install TensorFlow by following the instructions on this website: https://www.tensorflow.org/install/install_windows
    • Download and install Keras by following the instructions on this website: https://keras.io/#installation
    Overview
    The Beginning Application Development with TensorFlow and Keras course covers the development of a real-world application powered by TensorFlow and Keras. TensorFlow is popular software created by Google (and open source contributors) to facilitate the development of machine learning applications, particularly those that use deep learning. Keras is an interface that facilitates the development of deep learning models. The course starts with a hands-on introduction to TensorFlow and Keras. Then we move to the architecture of an example model, selecting the right layers to solve an example problem (predicting Bitcoin prices). Then we move on to the training and evaluation of the model. We will finish by deploying the model as a real-world product: a web-application (with an HTTP API) that uses Flask to make our model predictions available to the world.  

    This is a 2-day course packaged with the right balance of theory and hands-on activities that will help you easily learn TensorFlow and Keras from scratch.

    This course will provide you with a blueprint of how to build an application that generates predictions using a deep learning model. From there you can continue to improve the example model”either by adding more data, computing more features, or changing its architecture”continuously increasing its prediction accuracy, or create a completely new model, changing the core components of the application as you see fit.

    Lesson 1: Introduction to Neural Networks and Deep Learning

    • What are Neural Networks?
    • Configuring a Deep Learning Environment

    Lesson 2: Model Architecture

    • Choosing the Right Model Architecture
    • Using Keras as a TensorFlow Interface

    Lesson 3: Model Evaluation and Evaluation

    • Model Evaluation
    • Hyperparameter Optimization

    Lesson 4: Productization

    • Handling New Data
    • Deploying a Model as a Web Application

    This course is designed for developers, analysts, and data scientists interested in developing applications using TensorFlow and Keras.

    Hardware:
    For successful completion of this course, students will require computer systems with the following:

    • Processor: 2.6 GHz or higher, preferably multi-core
    • Memory: 4 GB RAM
    • Hard disk: 10 GB
    • Projector
    • Internet connection

     

    Software:

    • Operating System: Windows (8 or higher).
    • Visual Studio Code:https://code.visualstudio.com
    • Python 3: Follow instructions on the website: https://www.python.org/downloads/
    • TensorFlow 1.4 or higher on Windows: Follow instructions in website: https://www.tensorflow.org/install/install_windows
    • Keras 2: Follow instructions on the website (Keras only): https://keras.io/#installation

     

    Installation and Setup

    • Download and install Visual Studio Code from this website: https://code.visualstudio.com/
    • Download and install Python 3 from this website: https://www.python.org/downloads/
    • Download and install TensorFlow by following the instructions on this website: https://www.tensorflow.org/install/install_windows
    • Download and install Keras by following the instructions on this website: https://keras.io/#installation
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