Python continues to lead the way when it comes to Machine Learning, AI, Deep Learning and Data Science tasks. Because of this, we've decided to start a series investigating the top Python libraries across several categories: Of course, these lists are entirely subjective as many libraries could easily place in multiple categories. For example, Keras is included in this list but TensorFlow has been omitted and features in the Deep Learning library collection instead. This is because Keras is more of an'end-user' library like SKLearn, as opposed to TensorFlow which appeals more to researchers and Machine Learning engineer types. Now, let's get onto the list (GitHub figures correct as of October 3rd, 2018): "scikit-learn is a Python module for machine learning built on NumPy, SciPy and matplotlib. It provides simple and efficient tools for data mining and data analysis. SKLearn is accessible to everybody and reusable in various contexts. "Keras is a high-level neural networks API, written in Python and capable of running on top of TensorFlow, CNTK, or Theano.
Nov-26-2019, 01:05:03 GMT