SCHEDULE
May 18, 2022
No avaliable slots
INFO
PYTORCH TRAINING COURSE
PyTorch training course is Instructor-led and guided and is being delivered for 16 Hours over 4 weeks, 8 sessions, 2 sessions per week, 2 hours per session.
Instructor-led and guided training
Practical Hands-On, Highly Interactive training
This course will be taught in English language
All Published Ticket Prices are in US Dollars
4 Weekends PyTorch Training Schedule
October 24, 2020 - November 15, 2020 US Pacific time
4 Weekends | 2 hours on Saturdays, 2 hours on Sundays every weekend | US Pacific Time
8:30 AM - 10:30 AM US Pacific time each of those days
Please click here to add your location and find your local date and time for the 1st session to be held on October 24, 2020 at 8:30 AM US Pacific Time
Features and Benefits
16 Hours, 8 sessions, 4 weeks of total Instructor-led and guided training
Training material, instructor handouts and access to useful resources on the cloud provided
Practical Hands-on Lab exercises provided
Actual code and scripts provided
Real-life Scenarios
Course Objectives
This PyTorch training covers first the features of PyTorch, its pros and cons, and comparison with other alternatives, it then starts with the fundamentals of PyTorch. This training on PyTorch further covers Linear regression, Logistic regression, Neural networks, CNN, RNN, etc with the context of PyTorch.
Prerequisites
If you do not have any of these prerequisite skills we will be happy to teach you these skills for additional cost before you take this training course.
Python Programming Language
Conditional statements
Lists, Tuples in Python, dictionary
Object-oriented programming
List comprehension
Generators in python
Who can take PyTorch Training Course?
IT Professionals
Course Outline
1. Introduction to PyTorch
Why PyTorch
Tensorflow vs Pytorch vs Keras
Matrix Basics
Reproducibility
GPU and CPU Toggling
2. PyTorch Fundamentals
Basic Mathematical Tensor Operations
PyTorch Tensors
Two-Dimensional Tensors
Variables and Gradients
Practical Applications Using PyTorch
3. Linear Regression PyTorch Way
What is Linear Regression
Linear Regression in PyTorch
Linear Regression From CPU to GPU in PyTorch
Multiple Input Output Linear Regression
4. Logistic Regression with PyTorch
Logistic Regression for classification
Going deeper into Logistic Regression
Logistic Regression with PyTorch
From CPU to GPU in PyTorch
5. Basic Neural Network with PyTorch
Hidden Layers
Backpropagation
Activation Functions
Non-linearity
Feedforward Neural Network in PyTorch
More Feedforward Neural Network Models in PyTorch
Feedforward Neural Network From CPU to GPU in PyTorch
6. Convolutional Neural Network (CNN) with PyTorch
Feedforward Neural Network Transition to CNN
One Convolutional Layer
Multiple Convolutional Layers Overview
Pooling Layers
Padding for Convolutional Layers
Output Size Calculation
CNN in PyTorch
More CNN Models in PyTorch
Expanding CNN Model's Capacity
From CPU to GPU in PyTorch
Pre-trained CNNs
7. Recurrent Neural Networks (RNN) with PyTorch
Introduction to RNN
RNN in PyTorch
More RNN Models in PyTorch
RNN From CPU to GPU in PyTorch
8. Long Short-Term Memory Networks (LSTM) with PyTorch
Introduction to LSTMs
LSTM Equations
LSTM in PyTorch
More LSTM Models in PyTorch
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LOCATION Dubai - Dubai - United Arab Emirates
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