This very repository contains my AI & Data Science learning paths as followa:
- Data processing by Python and a bit SQL
packages or libraries: Pandas, NumPy, Matplotlib - Machine Learning algorithms (mainly on supervised learning) implemented by Python
packages or libararies: Scikit-Learn, SciPy - Deep learning algortihms implemented by Python
packages or libraries: TensorFlow, Keras, Scikit-Learn, Pandas, Matplotlib, NumPy
| Learning Types | Algorithms |
|---|---|
| Multiple Linear Regression | |
| Logistic Regression | |
| K-Nearest Neighbours (KNN) | |
| Supervised Learning | Support Vector Machine (SVM) |
| Naïve Bayes Classifier | |
| Decision Tree | |
| Random Forest | |
| Unsupervised Learning | K-Means Clustering |
- Perceptron Learning Algorithm (PLA)
- Artificial Neural Network (ANN)
- Convolutional Neural Network (CNN)
- Multi-task Cascade Convolution Neural Network (MTCNN) for Face Detection
- FaceNet Inception Module for Facial Feature Extraction
- Recurrent Neural Network (RNN): Natural Language Processing (e.g. Language Translation, Image Captioning, Conversational Models, Text Summarisation) - Ongoing
- Seq2seq Network
- Long Short-Term Memory (LSTM): Word Suggestion in Chatbot Systems, Unsegmented & Connected Handwriting Recognition, Speech Recognition, Google Translate - Ongoing
- Gated Recurrent Unit (GRU)