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Machine Learning Labs

(ML-LABS.AA1) / ISBN : 978-1-64459-455-1
This course includes
Hands-On Labs
AI Tutor (Add-on)
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About This Course

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.

Skills You’ll Get

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1

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
2

NumPy

  • Creating a Multi-Dimensional Array Using numpy
  • Creating a One-Dimensional Array Using numpy
3

Visualization Libraries

  • Creating a Scatter Plot Using matplotlib
4

Machine Learning Libraries

  • Using scikit-learn
  • Applying Box-Cox Transformation
5

Extracting, Transforming, and Loading Data

  • Handling the Missing Values
  • Performing Data Cleaning
6

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
7

Developing Classification Models

  • Performing Logistic Regression
  • Performing Bagging
  • Creating a Decision Tree
  • Creating a Confusion Matrix
  • Creating a Contingency Table
8

Developing Regression Models

  • Performing Linear Regression on the Salary Dataset
9

Developing Clustering Models

  • Performing K-Means Clustering

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