My path of learning AI. It is a more or less methodical approach to learning ML, DL and more.
├── 00_Coding
│ ├── 01_Linear Regression
│ ├── 02_Logistic Regression
│ ├── 03_SVM
│ ├── 04_Decision Tree
│ ├── 05_K-nearest neighbour
│ ├── 07_Naive Bayes
│ └── nltk library
├── 01_Machine Learning
│ ├── 00_Introduction
│ ├── 01_Supervised Algorithms
│ ├── 02_Optimisation Algorithms
│ ├── 04_Techniques and Terms
│ ├── 05_Model Evaluation
│ └── 06_Unsupervised Algorithms
├── 02_Deep Learning
│ ├── 00_Coding NNs
│ │ └── 01_MLP
│ ├── 01_Neural Networks
│ ├── 02_Deep Learning terminologies
│ └── 03_MLP
├── 03_Computer vision
├── 04_NLP
├── 05_Pytorch
│ └── FastAI
└── 06_Hugging_face