Posts

Neural Tangent Kernel, Every Model trained by GD is a kernel machine (Review)

Some QA from Deep Learning (CS 462/482)

NEURIPS 2020
Conference 
Adversarial NLP examples with Fast Gradient Sign Method
Code samples Instructional 
EMNLP 2020
Conference 
Variance of the Estimator in Machine Learning
Instructional 
Some Clustering Papers at ICLR20
Under construction 
A minimum keystroke (py)Debugger for Lazy ML/DS people who don't IDE
Code samples 
Recipe for building jq from source without admin(sudo) rights

The Sigmoid in Regression, Neural Network Activation and LSTM Gates
Instructional 
Arithmetic(Book)
Under construction Book Review 
Clean TreeLSTMs implementation in PyTorch using NLTK treepositions and EasyFirst Parsing
Code samples Instructional 
Pad pack sequences for Pytorch batch processing with DataLoader
Code samples Instructional 
Modes of Convergence
Instructional 
Coordinate Ascent Meanfield Variational Inference (Univariate Gaussian Example)
Code samples Instructional 
Dirichlet Process Gaussian Mixture Models (Generation)
Code samples 
Gotchas in Cython; Handling numpy arrays in cython class
Code samples 
Onboarding for Practical Machine Learning Research
Code samples 
Equivalence of constrained and unconstrained form for Ridge Regression
Instructional 
Studying drugdrug interactions and predictors of adverse vascular outcomes
Hackathon 
PyTorch Automatic differentiation for nonscalar variables; Reconstructing the Jacobian
Code samples Instructional 
From psychologist to CS PhD Student
Under construction Work experience 
Capturing Lastmile Transactions of Smallholder Palm Oil Farmers
Hackathon Code samples 
Migrating from python 2.7 to python 3 (and maintaining compatibility)
Work experience 
Lagrange Multipliers and Constrained Optimization
Under construction Instructional 
Taylor Series approximation, newton's method and optimization
Instructional 
Hessian, second order derivatives, convexity, and saddle points
Instructional 
Jacobian, Chain rule and backpropagation
Instructional 
Gradients, partial derivatives, directional derivatives, and gradient descent
Under construction Instructional 
Derivatives, differentiability and loss functions
Instructional 
Calculus for Machine Learning
Instructional 
Algorithms on Graphs: Fastest Route
Code samples Instructional 
Gibbs Sampling on Dirichlet Multinomial Naive Bayes (Text)
Code samples Instructional 
Markov Chain MonteCarlo
Under construction Instructional 
EM Algorithm for Gaussian mixtures
Code samples Instructional 
Communicating Data Science
Work experience 
Cross disciplinary projects
Work experience 
Conjugate Priors
Instructional 
Closed form Bayesian Inference for Binomial distributions
Code samples Instructional 
DSO Advice
Work experience 
Roles
Work experience
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