CCNA 200-301 Pearson uCertify Network Simulator
Cisco 200-301-SIMULATOR.AB1
CCNA 200-301 Pearson uCertify Network Simulator
ISBN: 978-1-61691-837-8Cisco 200-301-SIMULATOR.AB1
Machine Learning Labs
(ML-LABS.AA1) / ISBN : 978-1-64459-455-1
This course includes
Hands-On Labs
AI Tutor (Add-on)
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
Hands-On Labs
25+ LiveLab | 25+ Video tutorials | 27+ Minutes
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
