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.
- Price: $199.99
- Delivery method: eLearning
- DIR Discount: 20%
Submit form to obtain discount
Test Prep
Features
25+ LiveLab |
25+ Video tutorials |
27+ Minutes
Why choose TOPTALENT?
- Get assistance every step of the way from our Texas-based team, ensuring your training experience is hassle-free and aligned with your goals.
- Access an expansive range of over 3,000 training courses with a strong focus on Information Technology, Business Applications, and Leadership Development.
- Have confidence in an exceptional 95% approval rating from our students, reflecting outstanding satisfaction with our course content, program support, and overall customer service.
- Benefit from being taught by Professionally Certified Instructors with expertise in their fields and a strong commitment to making sure you learn and succeed.
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