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Applied Deep Learning with PyTorch
Level: Intermediate
Rating:
4.25/5 Based on 8 Reviews
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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LIVE, INSTRUCTOR-LED
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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- Delivered when, where, and how you want it
- Blended learning models
- Tailored content
- Expert team coaching
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In Class & Live, Online Training
Note: This course runs for 2 Days
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3 - 4 Nov 9:00 AM - 4:30 PM GMT Online (AnyWare)
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19 - 20 Jan 9:00 AM - 4:30 PM GMT Online (AnyWare)
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30 - 31 Mar 9:00 AM - 4:30 PM BST Online (AnyWare)
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8 - 9 Jun 9:00 AM - 4:30 PM BST Online (AnyWare)
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17 - 18 Aug 9:00 AM - 4:30 PM BST Online (AnyWare)
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8 - 9 Nov 2:00 PM - 9:30 PM GMT Herndon, VA / Online (AnyWare)
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7 - 8 Mar 2:00 PM - 9:30 PM GMT Ottawa / Online (AnyWare)
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9 - 10 May 2:00 PM - 9:30 PM BST Herndon, VA / Online (AnyWare)
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Guaranteed to Run
When you see the "Guaranteed to Run" icon next to a course event, you can rest assured that your course event — date, time — will run. Guaranteed.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
Team Training
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.