AI and Data Science Learning Path

Outline of Repository:

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

Machine Learning Algorithms:

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

Deep Learning Algorithms:

• 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)