Name		Name	Last commit message	Last commit date
Latest commit History 34 Commits
01_Bar_graph.ipynb		01_Bar_graph.ipynb
01_Basics_of_NumPy.ipynb		01_Basics_of_NumPy.ipynb
02_Operations_over_1D_Arrays.ipynb		02_Operations_over_1D_Arrays.ipynb
02_Scatterplot.ipynb		02_Scatterplot.ipynb
03_Line.ipynb		03_Line.ipynb
04_Histogram.ipynb		04_Histogram.ipynb
04_Multidimensional_Arrays.ipynb		04_Multidimensional_Arrays.ipynb
05_Box_plot.ipynb		05_Box_plot.ipynb
05_Creating_NumPy_Arrays.ipynb		05_Creating_NumPy_Arrays.ipynb
06_Subplots.ipynb		06_Subplots.ipynb
1_Getting_Data_I.ipynb		1_Getting_Data_I.ipynb
2_Getting_Data_II.ipynb		2_Getting_Data_II.ipynb
3_Handling_Missing_Data.ipynb		3_Handling_Missing_Data.ipynb
DS+in+Python+Movie+Assignment.ipynb		DS+in+Python+Movie+Assignment.ipynb
Day 3.ipynb		Day 3.ipynb
Day 4.ipynb		Day 4.ipynb
Day 5 .ipynb		Day 5 .ipynb
Day 6		Day 6
Jupyter+Notebook+Introduction+Session.ipynb		Jupyter+Notebook+Introduction+Session.ipynb
LICENSE		LICENSE
Pandas+Notebook+I.ipynb		Pandas+Notebook+I.ipynb
Pandas+Notebook+II.ipynb		Pandas+Notebook+II.ipynb
Pandas+Notebook+III.ipynb		Pandas+Notebook+III.ipynb
Pandas+Notebook+IV.ipynb		Pandas+Notebook+IV.ipynb
Pandas+Notebook+V.ipynb		Pandas+Notebook+V.ipynb
Practice+Exercise+1+IPL.ipynb		Practice+Exercise+1+IPL.ipynb
Practice+Exercise+1.ipynb		Practice+Exercise+1.ipynb
Python for ML Day 1.ipynb		Python for ML Day 1.ipynb
Python+Exercise+-+2+Part+(2).ipynb		Python+Exercise+-+2+Part+(2).ipynb
README.md		README.md
Session+1.ipynb		Session+1.ipynb
Session+2.ipynb		Session+2.ipynb
Session+3.ipynb		Session+3.ipynb
Session+4.ipynb		Session+4.ipynb
Untitled.ipynb		Untitled.ipynb
addresses.txt		addresses.txt
animal_farm.pdf		animal_farm.pdf
companies.PNG		companies.PNG
companies.txt		companies.txt
giphy.gif		giphy.gif
long.PNG		long.PNG
long.csv		long.csv
melbourne.csv		melbourne.csv
popularity.csv		popularity.csv
wide.PNG		wide.PNG
wide.csv		wide.csv

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Python_for_ML

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This repository serves as a learning and practice ground for Python-based machine learning (ML) projects. It includes a collection of Jupyter notebooks, scripts, and resources covering fundamental to advanced concepts in ML, with hands-on examples and exercises. Whether you're a beginner exploring the basics or an experienced practitioner looking f

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MIT license