2018

• Signal denoising using RNNs in PyTorch (13 Jan)
• CS Ph.D. lessons to my younger self (7 Jan)

2017

• Neural Networks for Collaborative Filtering (29 Dec)
• Recommender Systems in Keras (18 Dec)
• Adagrad based matrix factorization (13 July)
• Programatically understanding Adagrad (12 July)
• Top 50 ggplot2 Visualizations in Python - Part 1 (2 July)
• Linear regression with prior (using gradient descent) (15 June)
• Data exploration using widgets in Matplotlib (14 June)
• Hacking my way to a Jupyter notebook powered blog (10 June)
• Constrained Non-negative matrix factorisation using CVXPY (21 April)
• Out of Tensor factorisation (20 April)
• Out of matrix non-negative matrix factorisation (19 April)
• Non-negative matrix factorization with missing entries using CVXPY (7 April)
• Tensor decomposition using Autograd (6 April)
• Non-negative matrix factorization using Autograd (3 April)
• Non-negative matrix factorization using Tensorflow (2 April)
• Non-negative linear regression using Tensorflow (1 April)
• Non-negative matrix factorisation using non-negative least squares (29 March)
• Defended my PhD thesis (10 April)

2016

• Dummies guide to Fourier Transforms (29 March)
• Pythor- Python meets R (2 Jan)
• Interfacing NILM algorithms written in Matlab with NILMTK
• Understanding the HES data set

2014

• Hart's unsupervised NILM
• Understanding Statistical Distributions
• LaTeXify Matplotlib: Matplotlib plots for publishing
• Coin tosses and MCMC
• Programatically understanding Expectation Maximization
• Programatically understanding dynamic time warping (DTW)

2013

• Denoising using least squares
• Gibbs sampling- Hands on tutorial
• HMM Simulation for Continuous HMM
• HMM Simulation for Unfair Casino Problem
• Aggregation in Timeseries using Pandas
• Downloading weather data in Python