We have a separate page for fundamental python data science tooling – that is, the tools you are almost certain to use if you work with Python and data science.
This page covers tooling that is almost fundamental but there are options you may choose from. You’ll likely use one or more of these applications but not necessarily all of them.
PyTorch vs Tensorflow
- Ray Johns. PyTorch vs TensorFlow for Your Python Deep Learning Project. realpython, 9/2/2020.
- The Kite Team. Tensorflow or PyTorch? A Guide to Python Machine Learning Libraries (with examples!). kite, 10/25/18.
- PyTorch – Stars: 46.1k – Updated: 2/2021 – Checked: 2/2021 – Deep Learning.
- TensorFlow – Stars: 153k – Updated: 2/2021 – Checked: 2/2021 – machine learning.
- TensorFlow Cookbook – Stars: 2.8k – Updated: 2/2020 – Checked: 2/2021.
- TensorFlow Examples – Stars: 39.9k – Updated: 12/2020 – Checked: 2/2021.
- TensorFlow Course – Stars: 15.4k – Updated: 11/2020 – Checked: 2/2021.
- Keras – Deep Learning Library, can run on top of TensorFlow, CNTK, Theano.
- Victor Zhou. Keras for Beginners: Implementing a Convolutional Neural Network. 2019.
- Nikolai Janakiev. Practical Text Classification with Python and Keras. realpython.
- Daniel Pyrathon. Practical Machine Learning with Python and Keras. kite, 1/30/19.
- Brad Solomon. Python Histogram Plotting: NumPy, Matplotlib, Pandas & Seaborn. realpython.
Natural Language Toolkit (NLTK)
- Natural Language Toolkit (NLTK) – Stars: 9.6k – Updated: 1/2021 – Checked: 2/2021 – “a suite of open source Python modules, data sets, and tutorials supporting research and development in Natural Language Processing.”
- Eleanor Stribling. Python, NLTK, and the Digital Humanities: Finding Patterns in Gothic Literature. kite, 10/4/18.