Teaching yourself deep learning is a long and arduous process. You need a strong background in linear algebra and calculus, good Python programming skills, and a solid grasp of data science, machine ...

[Brendan Herger] was warned that the process of publishing a Python package would be challenging. He relishes a challenge, however, and so he went at it with gusto. The exhausting process led him to ...

TensorFlow, Spark MLlib, Scikit-learn, PyTorch, MXNet, and Keras shine for building and training machine learning and deep learning models. If you’re starting a new machine learning or deep learning ...

Python libraries that can interpret and explain machine learning models provide valuable insights into their predictions and ensure transparency in AI applications. A Python library is a collection of ...

Deep learning, which is basically neural network machine learning with multiple hidden layers, is all the rage—both for problems that justify the complexity and high computational cost of deep ...

Data science and machine learning professionals have driven adoption of the Python programming language, but data science and machine learning are still lacking key tools in business and has room to ...