This content originally appeared on DEV Community and was authored by J Fowler
Here’s a list of useful python libraries if you are working in ML
pandas – The standard data analysis and manipulation tool
numpy – scientific computing library
seaborn – statistical data visualization
sklearn – basic machine learning and predictive analysis
CausalML – a suite of uplift modeling and causal inference methods
PyTorch – professional deep learning framework
PivotTablejs – Drag’n’drop Pivot Tables and Charts for Jupyter/IPython Notebook
LazyPredict – build and work with and compare multiple models
phidata – Build AI Assistants with memory, knowledge and tools.
Lux – automates visualization and data analysis
pycaret – low-code machine learning library. really nice
Cleanlab – for when you are working with messy data
drawdata – draw a dataset from inside Jupyter
pyforest – lazy import popular data science libs
streamlit – simple ui builder, useful for demonstrating ML results
This is just a snapshot. Let me know your favorites and I’ll add them.
Thanks!
This content originally appeared on DEV Community and was authored by J Fowler