This repository is designed as a comprehensive, step-by-step guide to mastering AI and Machine Learning, covering essential prerequisites, mathematical foundations, core algorithms, and advanced concepts. Each section is divided into topic-specific markdown files, making it easy to navigate and focus on individual skills.
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├── 01_PreRequisites
│ ├── 01_python.md
│ ├── 02_numpy.md
│ ├── 03_pandas.md
│ ├── 04_matplotlib.md
│ └── README.md
├── 02_Maths
│ ├── 01_probability.md
│ ├── 02_linear_algebra.md
│ ├── 03_statistics.md
│ ├── 04_derivatives.md
│ └── README.md
├── 03_AI_and_Classification
│ ├── 01_classification.md
│ ├── 02_ai.md
│ └── README.md
├── 04_Statistical_ML
│ ├── 01_linear_regression.md
│ ├── 02_logistic_regression.md
│ ├── 03_perceptron.md
│ ├── 04_knn.md
│ ├── 05_naive_bayes.md
│ ├── 06_decision_tree.md
│ ├── 07_random_forest.md
│ ├── 08_svm.md
│ ├── 09_gaussian_process.md
│ ├── 10_SOMs.md
│ ├── 11_pca.md
│ ├── 12_gradient_boosting.md
│ └── README.md
├── 05_Deep_Learning
│ ├── 01_neural_networks.md
│ ├── 02_hyperparameter_tuning.md
│ ├── 03_mnist.md
│ └── README.md
├── 06_Computer_Vision
│ └── README.md
├── 07_Natural_Language_Processing
│ └── README.md
├── 08_Generative_AI
│ └── README.md
├── 09_Advance_Models
│ └── README.md
├── 10_APIs
│ └── README.md
└── README.md