Applied Deep Learning with PyTorch

Level: Intermediate

Starting with the basics of deep learning and their various applications, Applied Deep Learning with PyTorch shows you how to solve trending tasks, such as image classification and natural language processing by understanding the different architectures of the neural networks.

Key Features of this Applied Deep Learning with PyTorch Course:

  • After-course instructor coaching benefit
  • After-course computing sandbox included
  • Learning Tree end-of-course exam included

You Will Learn How To:

  • Detect a variety of data problems to which you can apply deep learning solutions
  • Learn the PyTorch syntax and build a single-layer neural network with it
  • Build a deep neural network to solve a classification problem
  • Develop a style transfer model
  • Implement data augmentation and retrain your model
  • Build a system for text processing using a recurrent neural network

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In Class & Live, Online Training

  • 2-day instructor led training course
  • One-on-one after-course instructor coaching
  • Pay later by invoice -OR- at the time of checkout by credit card
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Standard £1295

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PRODUCT #1277

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In Class & Live, Online Training

Note: This course runs for 2 Days

  • 9 - 10 Mar 9:00 AM - 4:30 PM GMT London / Online (AnyWare) London / Online (AnyWare) Reserve Your Seat

  • 10 - 11 Feb 2:00 PM - 9:30 PM GMT Herndon, VA / Online (AnyWare) Herndon, VA / Online (AnyWare) Reserve Your Seat

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Important Applied Deep Learning with PyTorch Course Information

  • Requirements

    Some working knowledge of Python and familiarity with the basics of machine learning are a must. However, knowledge of NumPy and pandas will be beneficial, but not essential.

  • Who Should Attend This Course

    Applied Deep Learning with PyTorch is designed for data scientists, data analysts, and developers who want to work with data using deep learning techniques. Anyone looking to explore and implement advanced algorithms with PyTorch will also find this course useful.

Applied Deep Learning with PyTorch Course Outline

  • Lesson 1: Introduction to Deep Learning and PyTorch

    • Understanding Deep Learning
    • PyTorch Introduction
  • Lesson 2: Building Blocks of Neural Networks

    • Introduction to Neural Networks
    • Data Preparation
    • Building a Neural Network
  • Lesson 3: A Classification Problem Using DNN

    • Problem Definition
    • Dealing with an Underfitted or Overfitted Model
    • Deploying Your Model
  • Lesson 4: Convolutional Neural Networks

    • Building a CNN
    • Data Augmentation
    • Batch Normalization
  • Lesson 5: Style Transfer

    • Style transfer
    • Implementation of Style Transfer Using the VGG-19 Network Architecture
  • Lesson 6: Analysing the Sequence of Data with RNNs

    • Recurrent Neural Networks
    • Long Short-Term Memory Networks (LSTMs)
    • LSTM Networks in PyTorch
    • Natural Language Processing (NLP)
    • Sentiment Analysis in PyTorch

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Applied Deep Learning with PyTorch FAQs

  • Can I take this data science course online?

    Yes! We know your busy work schedule may prevent you from getting to one of our classrooms which is why we offer convenient online training to meet your needs wherever you want, including online training.

London / Online (AnyWare)
Herndon, VA / Online (AnyWare)
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