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Corrected typos

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Hi,

Stjepan from manning here. I've corrected typos in my previous contributions.

Thank you.

Best,
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@ -61,9 +61,9 @@ The following is a list of free and/or open source books on machine learning, st
- [Feature Engineering Bookcamp](https://www.manning.com/books/feature-engineering-bookcamp) - Maurucio Aniche - This book’s practical case-studies reveal feature engineering techniques that upgrade your data wrangling—and your ML results.
- [Metalearning: Applications to Automated Machine Learning and Data Mining](https://link.springer.com/content/pdf/10.1007/978-3-030-67024-5.pdf) - Pavel Brazdil, Jan N. van Rijn, Carlos Soares, Joaquin Vanschoren
- [Managing Machine Learning Projects: From design to deployment](https://www.manning.com/books/managing-machine-learning-projects) - Simon Thompson
- [Causal Machine Learning](https://www.manning.com/books/causal-machine-learning) - Robert Ness - Practical introduction to building AI models that can reason about causality.
- [Causal AI](https://www.manning.com/books/causal-machine-learning) - Robert Ness - Practical introduction to building AI models that can reason about causality.
- [Bayesian Optimization in Action](https://www.manning.com/books/bayesian-optimization-in-action) - Quan Nguyen - Book about building Bayesian optimization systems from the ground up.
- [Machine Learning Algorithms in Depth](https://www.manning.com/books/machine-learning-algorithms-in-depth)) - Vadim Smolyakov - Book about practical implementations of dozens of ML algorithms.
- [Machine Learning Algorithms in Depth](https://www.manning.com/books/machine-learning-algorithms-in-depth) - Vadim Smolyakov - Book about practical implementations of dozens of ML algorithms.
- [Optimization Algorithms](https://www.manning.com/books/optimization-algorithms) - Alaa Khamis - Book about how to solve design, planning, and control problems using modern machine learning and AI techniques.
- [Practical Gradient Boosting](https://www.amazon.com/dp/B0BL1HRD6Z) by Guillaume Saupin