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Pragmatic Data Curriculum

     Essential Tools      Practical Machine Learning      Advanced Machine Learning      AI with TensorFlow      Data Visualization

AI with TensorFlow

Artificial Intelligence with TensorFlow is an online training course that offers an introduction to neural networks, deep learning, machine learning, artificial intelligence and their many applications. This immersive, hands-on course teaches students the data science tools and techniques needed to build and test neural networks in TensorFlow using real-world data.

This course is optimal for those who have taken Essential Data Tools & Practical Machine Learning and desire to expand their knowledge of modeling and data science with TensorFlow.

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Business Benefits

Artificial intelligence allows your company to mine vast amounts of data to do extraordinary things. Make better, data-driven decisions that can impact every aspect of the business by using the right data science tools, technologies and techniques. Expand your company’s data-driven expertise with Artificial Intelligence with TensorFlow.

What You'll Learn

Get hands-on experience with practical techniques that can be put to work immediately in your business. Download the technical brief.

Building simple iterative
algorithms with TensorFlow

Introduction to TensorFlow

  • Linear models
  • Error metrics
  • Gradient descent
  • Tensors and operations
  • Automatic differentiation

    Optimization with computation graph

    • Computation graph
    • Using accelerators (GPUs/TPUs)

    Basic neural networks

    • The XOR problem
    • Logistic regression
    • Neural networks and hidden layers
    • Activation functions
    • Initial weights

    Develop larger networks and address the challenges associated with them.

    Deep neural networks

    • What is deep learning?
    • Keras API
    • TensorBoard

    Optimization

    • Stochastic gradient descent
    • Exploring the loss surface and learning curves
    • Overfitting
    • Regularization
    • Dropout
    • Batch normalization

    Begin your survey of advanced networks with convolutional neural networks.

    Convolutional networks

    • Convolutions
    • Convolutional neural networks
    • Building a network in Keras
    • Exercise: improving the network architecture
    • Pre-training CNNs (applications)

    The Inception Model and the Deep Dream Algorithm

    • Inception Model
    • Deep Dreams

    Adversarial Noise

    • Fooling Neural Networks
    • How to find adversarial noise
    • Putting it all together
    • Exercise: Extending immunity

    Explore more advanced network architectures with variational autoencoders.

    Variational autoencoders

    • Autoencoders
    • Variational autoencoders (VAEs)
    • Application: noise removal
    • Generating new images
    • Exercise: new numbers

    Recurrent neural networks

    • Backpropagation through time
    • Prediction types
    • Example: name classification
    • Long-short term memory
    • Example: Generating strata abstracts

    Ready to take on the future of data?

     Who Should Attend

    Data analysts, economists, researchers, software engineers, software developers or data engineers who want to deepen your understanding of artificial intelligence and neural networks

     Key Skills Covered

    TensorFlow, Keras, neural networks, overfitting, convolutional neural networks, recurrent neural networks, autoencoders, adversarial noise

     Prerequisites

    To achieve the greatest benefit from this course, attendees must successfully pass Essential Data Tools & Practical Machine Learning, or possess the following skills prior to attending:

    • Intermediate Python
    • Familiarity with linear algebra
    • Familiarity with statistical modeling
    • Basic familiarity with machine learning
    Earn a coveted data science certification upon successful completion of class project

    Pricing and Registration

    Online Training
    $1,495 USD
    For the Online Course


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    Want to know how major companies are utilizing machine learning and AI to improve their businesses? Check out this Data Science in 30 Minutes chat with Uber’s chief data scientist Zoubin Ghahramani as he discusses areas of research his team is working on to enhance the Uber experience.

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