My Notes While Learning Machine Learning Deep Learning Python Kaggle and everything

Source: Deep Learning on Medium

My Notes While Learning Machine Learning Deep Learning Python Kaggle and everything

Ok so wherever I see a python code that does ML stuff I see some libraries imported.

Here I will list them and summarize what they do. So whenever I forgot I can check here also maybe will be helpful for others too.

pandas: pandas is an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language.

numpy:NumPy is the fundamental package for scientific computing with Python. It contains among other things:

  • a powerful N-dimensional array object
  • sophisticated (broadcasting) functions
  • tools for integrating C/C++ and Fortran code
  • useful linear algebra, Fourier transform, and random number capabilities

matplotlib.pyplot: matplotlib.pyplot is a state-based interface to matplotlib. It provides a MATLAB-like way of plotting.

seaborn: Seaborn is a Python data visualization library based on matplotlib. It provides a high-level interface for drawing attractive and informative statistical graphics.

torch: PyTorch is a python package that provides two high-level features:
Tensor computation (like numpy) with strong GPU acceleration — Deep
Neural Networks built on a tape-based autograd system

keras: Keras is a high-level neural networks API, written in Python and capable of running on top of TensorFlow, CNTK, or Theano. It was developed with a focus on enabling fast experimentation. Being able to go from idea to result with the least possible delay is key to doing good research.

glob: The glob module finds all the pathnames matching a specified pattern according to the rules used by the Unix shell, although results are returned in arbitrary order.

cv2: Unofficial pre-built OpenCV packages for Python.

Albumentations: albumentations is a fast image augmentation library and easy to use wrapper around other libraries.

tqdm: Instantly make your loops show a smart progress meter — just wrap any iterable with tqdm(iterable), and you’re done!

gc: This module provides an interface to the optional garbage collector.