Imran Ahmad, Ph.D is a data scientist at the Advanced Analytics Solution Center (A2SC) within the Canadian federal government, where he builds and deploys machine learning systems for mission-critical applications. In his 2010 doctoral thesis, he introduced a linear programming-based algorithm for optimal resource assignment in large-scale cloud computing environments, work that anticipated many of the distributed systems challenges now central to agent deployment. In 2017, he pioneered the development of StreamSensing, a real-time analytics framework that has become the foundation of several research papers on processing multimedia data within machine learning paradigms.Dr. Ahmad holds a visiting professorship at Carleton University in Ottawa and is an authorized instructor for Google Cloud and Microsoft Azure. He is the author of the bestselling 50 Algorithms Every Programmer Should Know (Packt Publishing), which has been widely adopted in both academic curricula and industry training programs. His work on intelligent agent architectures reflects a sustained engagement with the algorithmic, distributed systems, and cognitive computing traditions that converge in the emerging discipline of agent engineering. Every pattern in this book has been tested against the production realities of latency, cost, reliability, and security that define real-world deployments.

• Table of ContentsOverview of Algorithms Data Structures used in AlgorithmsSorting and Searching AlgorithmsDesigning AlgorithmsGraph AlgorithmsUnsupervised Machine Learning AlgorithmsTraditional Supervised Learning AlgorithmsNeural Network Algorithms Algorithms for Natural Language ProcessingRecommendation EnginesData Algorithms CryptographyLarge Scale Algorithms Practical Considerations

Imran Ahmad, Ph.D is a data scientist at the Advanced Analytics Solution Center (A2SC) within the Canadian federal government, where he builds and deploys machine learning systems for mission-critical applications. In his 2010 doctoral thesis, he introduced a linear programming-based algorithm for optimal resource assignment in large-scale cloud computing environments, work that anticipated many of the distributed systems challenges now central to agent deployment. In 2017, he pioneered the development of StreamSensing, a real-time analytics framework that has become the foundation of several research papers on processing multimedia data within machine learning paradigms.Dr. Ahmad holds a visiting professorship at Carleton University in Ottawa and is an authorized instructor for Google Cloud and Microsoft Azure. He is the author of the bestselling 50 Algorithms Every Programmer Should Know (Packt Publishing), which has been widely adopted in both academic curricula and industry training programs. His work on intelligent agent architectures reflects a sustained engagement with the algorithmic, distributed systems, and cognitive computing traditions that converge in the emerging discipline of agent engineering. Every pattern in this book has been tested against the production realities of latency, cost, reliability, and security that define real-world deployments.

• Table of ContentsOverview of Algorithms Data Structures used in AlgorithmsSorting and Searching AlgorithmsDesigning AlgorithmsGraph AlgorithmsUnsupervised Machine Learning AlgorithmsTraditional Supervised Learning AlgorithmsNeural Network Algorithms Algorithms for Natural Language ProcessingRecommendation EnginesData Algorithms CryptographyLarge Scale Algorithms Practical Considerations

Imran Ahmad, Ph.D is a data scientist at the Advanced Analytics Solution Center (A2SC) within the Canadian federal government, where he builds and deploys machine learning systems for mission-critical applications. In his 2010 doctoral thesis, he introduced a linear programming-based algorithm for optimal resource assignment in large-scale cloud computing environments, work that anticipated many of the distributed systems challenges now central to agent deployment. In 2017, he pioneered the development of StreamSensing, a real-time analytics framework that has become the foundation of several research papers on processing multimedia data within machine learning paradigms.Dr. Ahmad holds a visiting professorship at Carleton University in Ottawa and is an authorized instructor for Google Cloud and Microsoft Azure. He is the author of the bestselling 50 Algorithms Every Programmer Should Know (Packt Publishing), which has been widely adopted in both academic curricula and industry training programs. His work on intelligent agent architectures reflects a sustained engagement with the algorithmic, distributed systems, and cognitive computing traditions that converge in the emerging discipline of agent engineering. Every pattern in this book has been tested against the production realities of latency, cost, reliability, and security that define real-world deployments.

• Table of ContentsOverview of Algorithms Data Structures used in AlgorithmsSorting and Searching AlgorithmsDesigning AlgorithmsGraph AlgorithmsUnsupervised Machine Learning AlgorithmsTraditional Supervised Learning AlgorithmsNeural Network Algorithms Algorithms for Natural Language ProcessingRecommendation EnginesData Algorithms CryptographyLarge Scale Algorithms Practical Considerations