Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
17 Hour(s) 0 Minute(s)
Language
English
Rating
1 views
Course Overview
Learn how to create state of the art neural networks for deep learning with Facebook's PyTorch Deep Learning library!
Welcome to the best online course for learning about Deep Learning with Python and PyTorch!
PyTorch is an open source deep learning platform that provides a seamless path from research prototyping to production deployment. It is rapidly becoming one of the most popular deep learning frameworks for Python. Deep integration into Python allows popular libraries and packages to be used for easily writing neural network layers in Python. A rich ecosystem of tools and libraries extends PyTorch and supports development in computer vision, NLP and more.
This course focuses on balancing important theory concepts with practical hands-on exercises and projects that let you learn how to apply the concepts in the course to your own data sets! When you enroll in this course you will get access to carefully laid out notebooks that explain concepts in an easy to understand manner, including both code and explanations side by side. You will also get access to our slides that explain theory through easy to understand visualizations.
In this course we will teach you everything you need to know to get started with Deep Learning with Pytorch, including:
NumPy
Pandas
Machine Learning Theory
Test/Train/Validation Data Splits
Model Evaluation - Regression and Classification Tasks
Unsupervised Learning Tasks
Tensors with PyTorch
Neural Network Theory
Perceptrons
Networks
Activation Functions
Cost/Loss Functions
Backpropagation
Gradients
Artificial Neural Networks
Convolutional Neural Networks
Recurrent Neural Networks
and much more!
By the end of this course you will be able to create a wide variety of deep learning models to solve your own problems with your own data sets.
So what are you waiting for? Enroll today and experience the true capabilities of Deep Learning with PyTorch! I'll see you inside the course!
-Jose
Course Content
- 12 section(s)
- 97 lecture(s)
- Section 1 Course Overview, Installs, and Setup
- Section 2 COURSE OVERVIEW CONFIRMATION CHECK
- Section 3 Crash Course: NumPy
- Section 4 Crash Course: Pandas
- Section 5 PyTorch Basics
- Section 6 Machine Learning Concepts Overview
- Section 7 ANN - Artificial Neural Networks
- Section 8 CNN - Convolutional Neural Networks
- Section 9 Recurrent Neural Networks
- Section 10 Using a GPU with PyTorch and CUDA
- Section 11 NLP with PyTorch
- Section 12 BONUS SECTION: THANK YOU!
What You’ll Learn
- Learn how to use NumPy to format data into arrays, Use pandas for data manipulation and cleaning, Learn classic machine learning theory principals, Use PyTorch Deep Learning Library for image classification, Use PyTorch with Recurrent Neural Networks for Sequence Time Series Data, Create state of the art Deep Learning models to work with tabular data
Skills covered in this course
Reviews
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BBruno Ranschaert
The course starts pretty good, everything clear, but from the moment where Jose starts talking about embeddings (48, 15:40) it seems to me that a part is missing in the course. The jump from pytorch to actual use for machine learning is so big, one cannot understand it from this course alone. Many concepts are introduced with some hand waving that you have to research yourself.
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PPouria Modaresi
no detailed explanations of most important things
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MMruttunjay Karemuragi
nice
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가가영 손
Yes. The lecture is useful for me.
