Machine-Learning

My personal repository for personal notes on machine learning algorithms and coursework report from COMS30007 Machine Learning 2018.

The contents of this repository consist of 5 essential aspects in machine learning in the form of Jupyter Notebooks: Data Pre-processing, Dimensionality Reduction, Supervised Learning, Unsupervised Learning, and Deep Learning. Each notebook contain example algorithms/models along with my notes on them, detailing their process, application, advantages, and disadvantages. More topics will be uploaded soon. The

• Data Pre-processing
• Dimensionality Reduction
  • Principal Component Analysis
  • Linear Discriminant Analysis
• Supervised Learning
  • Regression
    • Linear Regression
    • Polynomial Linear Regression
  • Classification
    • Logistic Regression (as a classifier)
    • K-NN
    • SVM
    • Naive Bayes
    • Decission Tree
    • Random Forest
• Unsupervised Learning
  • Clustering
    • K-Means Clustering
    • Hierarchical Clustering
• Deep Learning (folder)
  • Artificial Neural Network
  • Convolutional Neural Network
  • Recurrent Neural Network
  • AutoEncoders (In_progress)
  • SSD (In-progress)
• Reinforcement Learning (TBA) (TBA)
• Model Selection and Boosting (TBA)
• Associative-Rule Learning (TBA)
• Natural Language Processing (TBA)

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The coursework folder has my report on Bayesian Modelling and Inference with the assignment details on a separate pdf in each respective coursework folder.

Example of the topics covered within the assignment were generative models, non-parametric learning and representation, , Bayesian Optimisation, and Gaussian Processes in the Bayesian Modelling coursework. Whilst approximate inference using ICM, MCMC, Mean Field Variational Inference and Variational AutoEncoders (VAE) were covered in the Inference coursework. Both report achieved high first class mark.

I've also recently setuped a blog on machine learning and AI. Head to https://fz16336.github.io/Learning-Page/ to see the progress so far. I intend to fill this blog with thought provoking articles on the history/philosophy/ and future of AI and robotics.