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This course introduces Python libraries used in machine learning for scientific computing, data analysis, visualization, and model development. It demonstrates workflows with SciPy, NumPy, pandas, Matplotlib, Seaborn, and scikit-learn.
Syllabus
- Course Introduction.
- Agenda.
- Scipy in Python.
- NumPy Tutorial.
- Uses of Pandas.
- Python Pandas.
- Matplotlib.
- Seaborn.
- Scikit Learn.
- Summary.
Taught by
Great Learning
Reviews
5.0 rating, based on 1 Class Central review
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The introductory Python library course provided a solid foundation in essential concepts. The curriculum covered key libraries, equipping me with the skills to manipulate data effectively. I gained proficiency in pandas for data analysis, matplotlib for visualization, and numpy for numerical operations. The hands-on exercises facilitated practical learning, while the instructors' clear explanations enhanced comprehension. The course offered a balanced mix of theory and practical application, enhancing my confidence to write code independently. Overall, the course was an insightful journey into the fundamental Python libraries, equipping me with practical skills essential for data manipulation and analysis.