- Top 20 Python libraries for data science in 2018 https://www.medium.com/activewizards-machine-learning-company/top-20-python-libraries-for-data-science-in-2018-2ae7d1db8049/?amp%3Butm_campaign=python_2018&%3Butm_medium=learnmachinelearning 3 comments learnmachinelearning
Linked pages
- TensorFlow http://tensorflow.org/ 440 comments
- PyTorch http://pytorch.org/ 100 comments
- Bokeh documentation — Bokeh 2.4.3 Documentation http://bokeh.pydata.org/en/latest/ 66 comments
- Scrapy | A Fast and Powerful Scraping and Web Crawling Framework https://scrapy.org/ 49 comments
- Keras: the Python deep learning API https://keras.io 46 comments
- Matplotlib — Visualization with Python http://matplotlib.org/ 45 comments
- pandas - Python Data Analysis Library http://pandas.pydata.org/ 34 comments
- spaCy · Industrial-strength Natural Language Processing in Python https://spacy.io/ 29 comments
- NumPy https://numpy.org 17 comments
- NLTK :: Natural Language Toolkit http://www.nltk.org/ 9 comments
- scikit-learn: machine learning in Python — scikit-learn 1.3.1 documentation http://scikit-learn.org/stable/index.html 1 comment
- Top 15 Python Libraries for Data Science in 2017 | ActiveWizards: data science and engineering lab https://activewizards.com/blog/top-15-libraries-for-data-science-in-python/ 1 comment
- Gensim: Topic modelling for humans https://radimrehurek.com/gensim/ 0 comments
- Top 20 Python libraries for data science in 2018 | ActiveWizards: data science and engineering lab https://activewizards.com/blog/top-20-python-libraries-for-data-science-in-2018/ 0 comments
- GitHub - catboost/catboost: A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU. https://github.com/catboost/catboost 0 comments
- Welcome to ELI5âs documentation! — ELI5 0.11.0 documentation https://eli5.readthedocs.io/en/latest/index.html 0 comments
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