Practical Data Science Using Python
Apply Data Science Using Python, Statistical Techniques, EDA, NumPy, Pandas, Scikit Learn, and Statsmodel Libraries
Created by Manas Dasgupta
Explore practical data science skills using Python, focusing on real-world data analysis and predictive modeling. Dive into statistical techniques, exploratory data analysis, and machine learning workflows with popular Python libraries. Build confidence in handling data challenges and optimizing models for better results.
Packt | Aug 2022 | 1786 min
What You Will Learn
You will work through hands-on projects and examples that guide you from data exploration to building and optimizing predictive models. By applying statistical methods and machine learning algorithms, you will practice using Python libraries to solve real data problems and evaluate your results with proven techniques.
Key Features
- Analyze and visualize data using NumPy, Pandas, and EDA techniques
- Build and evaluate machine learning models with scikit-learn and statsmodels
- Apply model optimization methods like hyperparameter tuning and cross-validation
Target Audience
Ideal for data analysts, aspiring data scientists, and Python developers who want to deepen their practical skills. If you have some programming experience and are ready to move beyond basics, you will gain the tools and confidence needed to tackle data science projects and improve your machine learning workflow.
