PyTorch for Deep Learning with Python Bootcamp
Learn how to create state of the art neural networks for deep learning with Facebook's PyTorch Deep Learning library!
4.60 (5279 reviews)
36 265
students
17 hours
content
Sep 2023
last update
$124.99
regular price
What you will 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
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Our Verdict
The PyTorch for Deep Learning with Python Bootcamp offers a thorough exploration of Facebook's PyTorch library and deep learning concepts, with a balance between hands-on coding and theoretical understanding. While some users suggest deeper dives into certain topics and installation improvements, the course is still an effective and comprehensive starting point for mastering deep learning techniques with PyTorch.
What We Liked
- Comprehensive coverage of PyTorch deep learning library, including image classification, recurrent neural networks, and tabular data modeling
- Effective explanation of theory concepts with practical examples, making it easier to understand and retain knowledge
- Well-structured course, great for building a strong foundation in machine learning without focusing solely on specific frameworks or applications
- Valuable feedback and support from instructors and teaching assistants on Udemy platform
Potential Drawbacks
- Some users mention the lack of depth in certain theoretical concepts; additional resources might be needed for thorough understanding
- Prerequisites for theory knowledge are not explicitly stated, assuming foundational machine learning concepts as known
- Installation issues due to outdated course files may pose a challenge; seeking alternative installation assistance could be necessary
- Exercises primarily involve copying and pasting lecture code without deviating from the lessons code content
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2373814
udemy ID
18/05/2019
course created date
03/08/2019
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