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Machine Learning Labs

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.

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Test Prep
Features
25+ LiveLab | 25+ Video tutorials | 27+ Minutes

Why choose TOPTALENT?

Outline

Lessons 1:
Pandas

  • About DataFrames
  • Creating DataFrames
  • Interacting with DataFrame Data
  • Manipulating DataFrames
  • Manipulating Data
  • Interactive Display
  • Summary

Lessons 2:
NumPy

  • Installing and Importing NumPy
  • Creating Arrays
  • Indexing and Slicing
  • Element-by-Element Operations
  • Filtering Values
  • Views Versus Copies
  • Some Array Methods
  • Broadcasting
  • NumPy Math
  • Summary

Lessons 3:
Visualization Libraries

  • matplotlib
  • Seaborn
  • Plotly
  • Bokeh
  • Other Visualization Libraries
  • Summary

Lessons 4:
Machine Learning Libraries

  • Popular Machine Learning Libraries
  • How Machine Learning Works
  • Learning More About Scikit-learn
  • Summary

Lessons 5:
Extracting, Transforming, and Loading Data

  • Topic A: Extract Data
  • Topic B: Transform Data
  • Topic C: Load Data
  • Summary

Lessons 6:
Designing a Machine Learning Approach

  • Topic A: Identify Machine Learning Concepts
  • Topic B: Test a Hypothesis
  • Summary

Lessons 7:
Developing Classification Models

  • Topic A: Train and Tune Classification Models
  • Topic B: Evaluate Classification Models
  • Summary

Lessons 8:
Developing Regression Models

  • Topic A: Train and Tune Regression Models
  • Topic B: Evaluate Regression Models
  • Summary

Lessons 9:
Developing Clustering Models

  • Topic A: Train and Tune Clustering Models
  • Topic B: Evaluate Clustering Models
  • Summary