Post Ideas: A guide to learn Python Frameworks

Ptython skills:

python libraries for data science & machine learning (pandas, numpy, scikit-learn)
data crunching and exploratory data analysis
supervised learning: classification and regression models
visualization tools in python environments (matplotlib, seaborn, plotly, bokeh, etc.)
Bayesian models in statistics
Deep Learning frameworks (torch, keras, tensorflow)
Computer Vision libraries (OpenCV)
Big data ecosystems

jmgomez-IAA / loogbook