This repository, arifpucit/data-science, is a curated collection of Jupyter notebooks, datasets, and other resources aimed at providing comprehensive learning in Data Science and Machine Learning.
Section-1: Overview of Data Science and Machine Learning concepts—tools, techniques, and technologies.Section-2: Basics of Python Programming for Data Science (recommended for those new to Python).Section-3: Applied Python Libraries for Data Science (NumPy, pandas, SciPy, statsmodels, scikit-learn, Matplotlib, Seaborn, and more).Section-4: Core Mathematics for Data Science.Section-5: Data Acquisition techniques and workflows.Section-6: Machine Learning fundamentals and practical implementations.Section-7: Natural Language Processing (NLP) concepts and applications.Section-8: Deep Learning principles and hands-on exercises.
Each section contains instructional notebooks and supporting resources.
- Comprehensive Curriculum: Covers foundational to advanced topics, including programming, mathematics, and specialized domains like NLP and deep learning.
- Hands-On Learning: Jupyter notebooks allow for interactive exploration and experimentation.
- Instructor’s Additional Resources: For lecture slides and further materials, visit Dr. Muhammad Arif Butt’s personal site: arifbutt.me.
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Clone the Repository
git clone https://github.com/arifpucit/data-science.git cd data-science