Library of Alexandria
Alex’s Pick
The Drug Hunters: The improbable Quest to Discover New Medicines
Delve into the thrilling quest for new medicines. Experience the challenges and successes of drug discovery.
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Modeling Mindsets: The Many Cultures of Learning From Data
Understand the varied approaches to data interpretation. Delve into the cultures and perspectives shaping data insights.
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Python Machine Learning
Dive deep into machine learning using Python. Techniques, algorithms, and practical applications unpacked.
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Experimental Design for Biologists
A guide to designing rigorous biological experiments. Learn to ensure replicability and accuracy.
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Python for Biologists: A complete programming course for beginners
An introductory programming guide catered to biologists. Learn Python from scratch with a biological twist.
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Deep Learning for the Life Sciences: Applying Deep Learning to Genomics, Microscopy, Drug Discovery, and More
Understand how deep learning is transforming the biological sciences. Discover its applications in genomics, drug discovery, and more.
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Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems
Dive into practical machine learning using Scikit-Learn and TensorFlow. A comprehensive guide to building intelligent systems.
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Bioinformatics Data Skills: Reproducible and Robust Research with Open Source Tools
Learn the essentials of bioinformatics data management. Explore best practices for analysis using open-source tools.
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R Graphics Cookbook: Practical Recipes for Visualizing Data
This guide offers techniques for visual data representation using R. Learn to create impactful visualizations with practical recipes.
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An Introduction to Statistical Learning: with Applications in R
Learn modern statistical methods with practical applications in R. A comprehensive guide for budding statisticians.
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R Cookbook: Proven Recipes for Data Analysis, Statistics, and Graphics
This is a practical guide for data analysis using R. It offers solutions and recipes for common statistical tasks.
