What you’ll learn
- Data Processing and Importing: Learn to handle and import raw data efficiently using Python.
- Exploratory Data Analysis (EDA): Master the art of exploratory data analysis, gaining insights into patterns, trends, and outliers within the data.
- Data Splitting and Model Evaluation: Understand the importance of data splitting for model training and evaluation.
- Hyperparameter Tuning: Explore techniques for optimizing model performance through hyperparameter tuning.
- Decision Tree Theory and Implementation: Grasp the foundational concepts of decision trees in machine learning.
- Graph Visualization and Decision Tree Interpretation: Install and utilize Graphviz for visualizing decision trees.
- Real-World Project Application: Apply acquired skills in a real-world data science project.
- Practical Python Coding Skills: Develop hands-on coding proficiency in Python, specifically tailored for data analysis and machine learning.
How to Enroll Python Data Analysis Project: From Raw Data to Decision Tree course?
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