Troubleshooting Python Deep Learning [Video]

More Information
Learn
  • Go through curated issues that many developers face when building their deep learning models
  • Discover the most efficient techniques to overcome classification problems in CNN
  • Resolve issues that are related to the CNN architecture, accuracy, input, and output
  • Work with LSTM, which is a part of RNN, and deal with the most efficient part of text problems
  • Discover how to solve the most popular problems from architecture to input and output
  • Implement the most usable libraries, scikit-learn and NumPy, to resolve the major problems arising from your Deep Learning models
About

Building Deep Learning models with Python is a strenuous task and there are chances of getting stuck on specific tasks. When that happens, you usually end up searching for solutions and need to manually look for ways to resolve these problems. This wastes both time and effort, and may also lead to reduced performance of your Deep Learning system.

After carefully analyzing the most popular errors or problems that arise while working on Deep Learning models, we have identified the most usable models used for classification in this course and provided practical yet unique solutions to each problem that are easy to understand and implement.

You can either follow the entire course or directly jump into the section that covers a specific problem you’re facing. Some of the common yet important issues we cover include errors while building and training Deep Learning with neural networks, especially without a specific framework.

By the end of the course, you will be well-versed to tackle and troubleshoot any errors with your Deep Learning models.

The code bundle for this video course is available at - https://github.com/PacktPublishing/Troubleshooting-Python-Deep-Learning

Features
  • Discover the limitless use of building any application using Deep Learning and ensure its issues aren’t a roadblock for your projects
  • Problems are addressed with practical yet unique solutions that are easy to understand and implement
  • Implement scikit-learn and NumPy, to resolve the common problems arising from Deep Learning models
Course Length 3 hours 2 minutes
ISBN 9781788998192
Date Of Publication 30 Apr 2019

Authors

Jakub Konczyk

Jakub Konczyk has enjoyed and programmed professionally since 1995. He is a Python and Django expert and has been involved in building complex systems since 2006. He loves to simplify and teach programming subjects and share this with others. He first discovered Machine Learning when he was trying to predict the real estate prices in one of the early stage start-ups, he was involved in. He failed miserably then. He then discovered a much more practical way to learn Machine Learning, which he would like to share with you in this course. It boils down to the “Keep it simple” mantra. He is the author of multiple bestselling video courses on Machine Learning and Deep Learning, including Real-World Deep Learning Python Projects and AI in Finance. Learn more at https://kubakonczyk.com/members/tffl