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Ervaar een blended learning-aanpak die het beste van door een instructeur geleide training en e-learning in eigen tempo combineert om u te helpen zich voor te bereiden op uw certificeringsexamen.

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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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Gecertificeerde medewerkers zijn GEWAARDEERDE activa. Verken de officiële Digital Learning Library van Cisco om uzelf te informeren via opgenomen sessies.

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Het Cisco Business Enablement Partner Program richt zich op het aanscherpen van de zakelijke vaardigheden van Cisco Channel Partners en klanten.

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Het Cisco Business Enablement Partner Program richt zich op het aanscherpen van de zakelijke vaardigheden van Cisco Channel Partners en klanten.

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Fortinet-certificering

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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Fortinet-training

Insoft is erkend als Fortinet Authorized Training Center op geselecteerde locaties in EMEA.

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Bekijk de volledige Fortinet trainingscatalogus. Het programma omvat een breed scala aan cursussen in eigen tempo en onder leiding van een instructeur.

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Insoft Services biedt Microsoft-trainingen in EMEAR. We bieden technische trainingen en certificeringscursussen van Microsoft aan die worden geleid door instructeurs van wereldklasse.

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Extreme-training

Find all the Extreme Networks online and instructor led class room based calendar here.

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Technische-certificering

We provide comprehensive curriculum of technical competency skills on the certification accomplishment.

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Leer uitzonderlijke kennis en vaardigheden van Extreme Networks

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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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