About This Book

“Tensor Programming in C: Building High-Performance Numerical Systems from Scratch” is your go-to guide for mastering tensor operations and building blazing-fast systems in C. Whether you’re starting with basic tensor structures or diving into neural networks and embedded systems, this book walks you through every step with clear, hands-on examples. My goal is to help you turn complex ideas into practical, high-performance code you can deploy anywhere.

The Author

I’m Mohit Mishra, a software engineer and machine learning enthusiast who’s spent years crafting efficient applications and tensor libraries in C and Python. I’ve worked on projects spanning tiny embedded devices to massive, scalable systems, always focusing on squeezing out every bit of performance.

With a mix of engineering know-how and a love for the theory behind computer science, I enjoy taking tricky concepts and turning them into clean, production-ready code. My work revolves around machine learning, MLOps, and competitive programming, and I’m no stranger to digging into manual memory management, optimizing performance, or debugging with tools like GCC, Valgrind, and GDB. When I’m not coding, you might find me experimenting with TensorFlow, Keras, or PyTorch to build something new.

Key Features of This Book

This book is written for C programmers who want to build high-performance systems from the ground up. It’s perfect if you’re:

• An embedded systems developer trying to run machine learning algorithms on low-power hardware
• A performance engineer tweaking code for HPC environments
• A machine learning developer curious about what’s happening under the hood of frameworks
• A computer science student eager to connect theoretical ideas with real-world coding

You’ll need some familiarity with C programming and basic linear algebra, but don’t worry—I explain everything from the basics, focusing on practical, step-by-step implementation.

Contact Information

Got questions, feedback, or spotted an error in the book? Feel free to reach out! You can email me at:
Email
Or connect with me on LinkedIn or X.