Sign up to save your podcasts
Or
Share Applied Deep Learning: A Case-Based Approach to Understanding Deep Neural Networks
Share to email
Share to Facebook
Share to X
Share to email
Share to Facebook
Share to X
Or
Applied Deep Learning: A Case-Based Approach to Understanding Deep Neural Networks
Guides readers through fundamental concepts of deep learning, including computational graphs, single neurons, and feedforward neural networks, often using TensorFlow for practical implementation. The author emphasizes understanding the mathematical underpinnings of algorithms, discusses optimization techniques like gradient descent and Adam, and addresses critical aspects such as regularization to combat overfitting, metric analysis for model evaluation, and hyperparameter tuning. Chapters further explore advanced network architectures like convolutional and recurrent neural networks, and demonstrate their application in real-world scenarios.
You can listen and download our episodes for free on more than 10 different platforms:
https://linktr.ee/cyber_security_summary
Get the Book now from Amazon:
https://www.amazon.com/Applied-Deep-Learning-Case-Based-Understanding-ebook/dp/B07H6D9NQ8?&linkCode=ll1&tag=cvthunderx-20&linkId=b12793360955b5dd9433db6c021197b7&language=en_US&ref_=as_li_ss_tl
You can listen and download our episodes for free on more than 10 different platforms:
https://linktr.ee/cyber_security_summary
Get the Book now from Amazon:
https://www.amazon.com/Applied-Deep-Learning-Case-Based-Understanding-ebook/dp/B07H6D9NQ8?&linkCode=ll1&tag=cvthunderx-20&linkId=b12793360955b5dd9433db6c021197b7&language=en_US&ref_=as_li_ss_tl
View all episodes
By CyberSecurity SummaryGuides readers through fundamental concepts of deep learning, including computational graphs, single neurons, and feedforward neural networks, often using TensorFlow for practical implementation. The author emphasizes understanding the mathematical underpinnings of algorithms, discusses optimization techniques like gradient descent and Adam, and addresses critical aspects such as regularization to combat overfitting, metric analysis for model evaluation, and hyperparameter tuning. Chapters further explore advanced network architectures like convolutional and recurrent neural networks, and demonstrate their application in real-world scenarios.
You can listen and download our episodes for free on more than 10 different platforms:
https://linktr.ee/cyber_security_summary
Get the Book now from Amazon:
https://www.amazon.com/Applied-Deep-Learning-Case-Based-Understanding-ebook/dp/B07H6D9NQ8?&linkCode=ll1&tag=cvthunderx-20&linkId=b12793360955b5dd9433db6c021197b7&language=en_US&ref_=as_li_ss_tl
You can listen and download our episodes for free on more than 10 different platforms:
https://linktr.ee/cyber_security_summary
Get the Book now from Amazon:
https://www.amazon.com/Applied-Deep-Learning-Case-Based-Understanding-ebook/dp/B07H6D9NQ8?&linkCode=ll1&tag=cvthunderx-20&linkId=b12793360955b5dd9433db6c021197b7&language=en_US&ref_=as_li_ss_tl