Machine Learning Labs

(ML-LABS.AA1)/ISBN:978-1-64459-455-1

This course includes
Hand-on Lab
AI Tutor (Add-on)

Experience the power of hands-on learning in Machine Learning Labs. This interactive course offers engaging lessons and immersive labs where you'll gain practical experience in performing various machine-learning tasks. From working with Pandas DataFrames to exploring visualization libraries and popular machine learning libraries like Scikit-learn, you'll develop the skills needed to excel in the dynamic field of machine learning.

Hand on lab

25+ LiveLab | 25+ Video tutorials | 27+ Minutes

Here's what you will learn

Download Course Outline

Hands-on LAB Activities

Pandas

  • Using the read_csv() Function
  • Filtering a DataFrame Based on Index
  • Indexing a DataFrame
  • Sorting a DataFrame
  • Creating a Series from a Dictionary Using pandas

NumPy

  • Creating a Multi-Dimensional Array Using numpy
  • Creating a One-Dimensional Array Using numpy

Visualization Libraries

  • Creating a Scatter Plot Using matplotlib

Machine Learning Libraries

  • Using scikit-learn
  • Applying Box-Cox Transformation

Extracting, Transforming, and Loading Data

  • Handling the Missing Values
  • Performing Data Cleaning

Designing a Machine Learning Approach

  • Performing Chi-Square Test
  • Performing Two-Way ANOVA
  • Calculating the Euclidean Distance between Two Series
  • Performing Feature Selection Using Chi-Square Test
  • Performing One-Way ANOVA
  • Performing the Goodness of Fit Test

Developing Classification Models

  • Performing Logistic Regression
  • Performing Bagging
  • Creating a Decision Tree
  • Creating a Confusion Matrix
  • Creating a Contingency Table

Developing Regression Models

  • Performing Linear Regression on the Salary Dataset

Developing Clustering Models

  • Performing K-Means Clustering