During development, cells make sequential decisions to change their state, eventually generating the tremendous cellular diversity in our body. To describe this process, Conrad Waddington proposed ...

Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep ...

Majority of modern techniques for creating and optimizing the geometry of medical devices are based on a combination of computer-aided designs and the utility of the finite element method This ...

Understanding the strengths and weaknesses of machine learning (ML) algorithms is crucial to determine their scope of application. Here, we introduce the Diverse and Generative ML Benchmark (DIGEN), a ...

If you are interested in pursuing a career in AI and don’t know where to start, here’s your go-to guide for the best programming languages and skills to learn, interview questions, salaries and more.

Genetic recombination processes, such as reassortment, make it complex or impossible to use standard phylogenetic and phylodynamic methods. This is due to the fact that the shared evolutionary history ...

Breeding programs depend on large-scale, accurate phenotyping, which is also critical for genomic dissection of complex traits. While the genome of an organism can be characterized, e.g., with high ...

NumPyCNN is a Python implementation for convolutional neural networks (CNNs) from scratch using NumPy. IMPORTANT If you are coming for the code of the tutorial titled Building Convolutional Neural ...