Create Machine Learning Models

October 2020

Setting up local environment

$ conda create -n ml-basics python=3.7

$ conda activate ml-basics

$ pip install jupyter

$ pip install matplotlib

$ pip install pillow

$ pip install requests

$ pip install numpy

$ pip install pandas

$ pip install scikit-learn

$ pip install scikit-image

$ pip install scipy

$ pip install torch==1.6.0+cpu torchvision==0.7.0+cpu -f https://download.pytorch.org/whl/torch_stable.html

$ pip install tensorflow

01 - Data Exploration

https://github.com/MicrosoftDocs/ml-basics/blob/master/01%20-%20Data%20Exploration.ipynb

df_students.query('Name=="Aisha"')


Create a bar plot of name vs grade

fig = plt.figure(figsize=(8,3))


plt.bar(x=df_students.Name, height=df_students.Grade, color='orange')


# Customize the chart

plt.title('Student Grades')

plt.xlabel('Student')

plt.ylabel('Grade')

plt.grid(color='#95a5a6', linestyle='--', linewidth=2, axis='y', alpha=0.7)

plt.xticks(rotation=90)


df_students.plot.bar(x='Name', y='StudyHours', color='teal', figsize=(6,4))

var_data.plot.density()

Create a bar plot of name vs grade and study hours

df_sample.plot(x='Name', y=['Grade','StudyHours'], kind='bar', figsize=(8,5))