AI for Scientific Discovery 1st Edition

Grab the future of research with AI for Scientific Discovery, 1st Edition by Janna Hastings. This authoritative guide bridges cutting-edge artificial intelligence with the practical needs of scientists, offering a clear roadmap for harnessing machine learning, data-driven modeling, and automated inference in real-world research.

Packed with readable explanations and domain-spanning examples, this volume unpacks core techniques—representation learning, causal inference, model interpretability, and reproducible workflows—so you can apply them across biology, chemistry, physics, and environmental science. Janna Hastings combines technical rigor with accessible prose to demystify complex concepts while emphasizing best practices for experimental design, data quality, and ethical AI.

Whether you’re a principal investigator at a university lab, a data scientist in industry, or a graduate student building multidisciplinary skills, this book delivers practical insights that accelerate discovery. Learn how to translate noisy experimental data into robust hypotheses, design interpretable models that collaborate with domain expertise, and scale analyses for high-throughput experiments. The global perspective makes it relevant for researchers in North America, Europe, Asia, and beyond.

Clear visuals, worked examples, and a focus on reproducibility make this an essential reference for anyone integrating computational intelligence into scientific workflows. If your goal is to stay at the forefront of research innovation, AI for Scientific Discovery, 1st Edition by Janna Hastings is the strategic resource to read now.

Add this indispensable guide to your collection and equip your team with the methods to turn data into discovery—order your copy today.

Note: eBooks do not include supplementary materials such as CDs, access codes, etc.