Skip to content

Fixed the link #145

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
wants to merge 1 commit into
base: master
Choose a base branch
from
Open

Fixed the link #145

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
2 changes: 1 addition & 1 deletion README.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -86,7 +86,7 @@ Contributions are welcome. Connect on [LinkedIn](https://www.linkedin.com/in/owa
* [MachineLearningWithTensorFlow2ed](https://www.manning.com/books/machine-learning-with-tensorflow-second-edition) is a book on general-purpose machine learning techniques, including regression, classification, unsupervised clustering, reinforcement learning, autoencoders, convolutional neural networks, RNNs, and LSTMs, using TensorFlow 1.14.1.
* [Serverless Machine Learning](https://www.manning.com/books/serverless-machine-learning-in-action) - a book for machine learning engineers on how to train and deploy machine learning systems on public clouds like AWS, Azure, and GCP, using a code-oriented approach.
* [The Hundred-Page Machine Learning Book](http://themlbook.com/) - all you need to know about Machine Learning in a hundred pages, supervised and unsupervised learning, SVM, neural networks, ensemble methods, gradient descent, cluster analysis and dimensionality reduction, autoencoders and transfer learning, feature engineering and hyperparameter tuning.
* [Trust in Machine Learning](https://www.manning.com/books/trust-in-machine-learning) - a book for experienced data scientists and machine learning engineers on how to make your AI a trustworthy partner. Build machine learning systems that are explainable, robust, transparent, and optimized for fairness.
* [Trustworthy Machine Learning](https://www.amazon.com/Trustworthy-Machine-Learning-Kush-Varshney/dp/B09SL5GPCD) - a book for experienced data scientists and machine learning engineers on how to make your AI a trustworthy partner. Build machine learning systems that are explainable, robust, transparent, and optimized for fairness.
* [Generative AI in Action](https://www.manning.com/books/generative-ai-in-action) - A book that shows exactly how to add generative AI tools for text, images, and code, and more into your organization’s strategies and projects..

## Programming
Expand Down