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MACHINE-LEARNING, TITANICS, AND GRAPHICS

Enviroment setup

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conda create --name diploma42
conda activate diploma42

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conda install -c anaconda pandas
conda install -c anaconda seaborn
conda install -c conda-forge matplotlib
pip install joblib


conda install -c anaconda keras 
pip install plotly-express
pip install dash
pip install psutil
conda install scikit-learn
netsh http add iplisten 127.0.0.1
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Execution to run

1. MINING ACCURACY PERCENTAGE 

python bankAll.py
python processory.py
python Students.py
python Titanic.py

2. SCHEDULING AND HTML-GRAPHICS

python continent.py
Python dashPlot.py
python scheduleA.py
python scheduleB.py

2. Plan-Intenational-Scheme 

python app1.py
python app2.py

Python Gantts and Plot of computations and graphs

Below are some screens shots from the computations console \

Open Monze-dataset for information on MATHERMATICAL package application.

 AM#01  AM#02  AM#03  AM#04  AM#05  AM#06  AM#07

Open Musamba-dataset for information for MACHINE-LEARNING package application.

 AM#08  AM#09  AM#10  AM#11  AM#12  AM#13  AM#14  AM#15  AM#16  AM#17

Open Pemba-dataset for information for ARTIFICIAL-NEURAL-NETWORK package application.

 AM#18  AM#19  AM#20  AM#21  AM#22  AM#23

Luska

 AM#24  AM#26  AM#27

Open Travel-dataset for PASSENGERS application.

 AM#28  AM#29  AM#30  AM#31

Version - Week #42

    10/09/2021

END!

About

1). ML and, 2). ANNs Techniques, Week#42

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