Posts
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Neural Tangent Kernel, Every Model trained by GD is a kernel machine (Review)
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Some QA from Deep Learning (CS 462/482)
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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
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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 Easy-First Parsing
Code samples Instructional -
Pad pack sequences for Pytorch batch processing with DataLoader
Code samples Instructional -
Modes of Convergence
Instructional -
Coordinate Ascent Mean-field 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 drug-drug interactions and predictors of adverse vascular outcomes
Hackathon -
PyTorch Automatic differentiation for non-scalar variables; Reconstructing the Jacobian
Code samples Instructional -
From psychologist to CS PhD Student
Under construction Work experience -
Capturing Last-mile 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 Monte-Carlo
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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