How mabdullah10/100-days-of-ml works
This repository is a notebook-based data science learning curriculum, not a single runtime application. A learner studies foundations, data acquisition and analysis, preprocessing, then modeling-related material. The tree identifies these topics, but there is no README and only the online-learning script was sampled; connections between individual lessons and their datasets or saved artifacts are therefore not asserted.
Main entry points: 001-python-basics.ipynb Python Basics · 002-Indexing--data-structures.ipynb Data Structures · 003 numpy-arrays(1d, 2d, 3d).ipynb NumPy Arrays · 004-pandas.ipynb Pandas
Components 17
Foundations
- Python Basics
001-python-basics.ipynb - Data Structures
002-Indexing--data-structures.ipynb - NumPy Arrays
003 numpy-arrays(1d, 2d, 3d).ipynb - Pandas
004-pandas.ipynb
Data Work
- Data Import
015-working-with-csv.ipynb - API and Scraping
017-fetching-data-from-api.ipynb - Data Understanding
019-understanding-your-data.ipynb - Exploratory Analysis
020-eda-using-univariate-analysis.ipynb - Multivariate Analysis
021-eda-using-multivariate-analysis.ipynb
Preprocessing
- Feature Scaling
024-feature-scaling-standardization.ipynb - Categorical Encoding
027-categorical-data--one-hot-encoding.ipynb - Pipelines
029.1-pipelines.ipynb - Missing Data
039-multivariate-imputation--knn-imputer.ipynb - Outlier Handling
043-outlier--iqr-method.ipynb
Modeling
- Online Learning
005-online-ml.py - Toy Project
013-toy-project.ipynb
Other components
- Learner
Connections 16
- Learner → Python Basics: studies
- Learner → Data Structures: studies
- Learner → NumPy Arrays: studies
- Learner → Pandas: studies
- Learner → Data Import: studies
- Learner → API and Scraping: studies
- Learner → Data Understanding: studies
- Learner → Exploratory Analysis: studies
- Learner → Multivariate Analysis: studies
- Learner → Feature Scaling: studies
- Learner → Categorical Encoding: studies
- Learner → Pipelines: studies
- Learner → Missing Data: studies
- Learner → Outlier Handling: studies
- Learner → Online Learning: studies
- Learner → Toy Project: studies