Data Science in Python: From Preprocessing to Forecasting
From preprocessing intricacies to advanced forecasting techniques. Equip yourself with the skills to navigate the data
4.45 (29 reviews)
3,910
students
2 hours
content
Mar 2024
last update
FREE
regular price
What you will learn
Data Preprocessing: Master techniques for effective data cleaning, formatting, and organization. Learn both basic data cleaning methods and advanced preproces
Data Preprocessing and Feature Engineering: Build on the fundamentals of data preprocessing.
Grasp the concept of feature engineering and its significance in enhancing model performance.
Gain practical insights and make informed decisions during the feature engineering process.
Graph Visualization - Components: Transition into the realm of data visualization.
Explore the components of graph visualization and their importance in representing and interpreting data.
Learn advanced features and customization options for creating compelling visualizations.
Training Model: Shift to practical aspects of model training. Understand modeling and evaluation fundamentals.
Validation and Forecasting: Acquire skills in model validation techniques. Explore forecasting methods to predict future trends based on historical data.
Producing and Visualizing Forecasts: Apply forecasting models to produce and visualize predictions. Learn visualization techniques to enhance interpretability
Comparing Models: Master the critical task of model comparison.
Explore strategies for evaluating and selecting the most effective model for specific use cases.
Installation of Library Prophet: Engage in practical, hands-on activities.
Creating a Model using Prophet: Immerse in the practical process of creating models using the Prophet library.
Evaluation of Model of Prophet Library: Focus on evaluating models created with the Prophet library.
5634854
udemy ID
10/30/2023
course created date
11/3/2023
course indexed date
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