Main Contents
-
Middle Aged Work Advice
Work Experiences -
Dynamic Batching for Training Large Sequence Models (LLMs)
Code PyTorch -
RAG System Architecture
Projects -
Vibe Coding Car Racing Simulator (Fail)
Code Misc -
Deriving the Basic Policy Gradient Update (REINFORCE)
Reinforcement Learning -
Data Extraction for Unstructured Document Data
Projects -
First 100 words
Misc -
Temporal Difference Learning: Taking advantage of Incomplete Trajectories
Reinforcement Learning -
Synthetic Question Generation for Retrieval Evaluation of RAG
-
Deriving the minimax equation for GANs
Generative Models -
Chunking code for RAG; parsing-recursion-stack
Code -
A classical NLP researcher and a GPT-era Engineer meet at the coffee machine
Generative Models -
Python Decorators for Monitoring GPU Usage
Code PyTorch -
A baby and a PhD
Work Experiences -
LLM Research and Adaptation Landscape
Generative Models -
Monitoring Jobs on the Server
Code -
Taking a break from NLP Research
Work Experiences -
Lean OmegaConf Argparse System
Code -
Training Sparse Neural Networks with L0 Regularisation
Machine Learning -
Dynamic Programming for Reinforcement Learning, the importance of the Bellman equations; (with Gymnasium)
Reinforcement Learning -
Could Large Language Models be conscious? (David Chalmers @ Neurips 2022)
Misc -
NLP Papers at ICML2022
Review -
You don't feel like you're good enough, but its not a competition
Work Experiences -
Stochastic Gradient Langevin Dynamics
Bayesian Inference Machine Learning Optimization -
NYCMidnight-100words
Misc -
Recipe for connecting to Google Drive from Remote Server
Code -
Minimum Bayes Risk Decoding
Bayesian Inference -
Formalising Analogies for A.I
Machine Learning -
You're not doing well, but motivation is optional
Work Experiences -
Likelihood weighted Sequential Importance Sampling
Machine Learning -
Neural Tangent Kernel, Every Model trained by GD is a kernel machine (Review)
Review -
Some QA from Deep Learning (CS 462/482)
Machine Learning -
NEURIPS 2020
Review -
Adversarial NLP examples with Fast Gradient Sign Method
Misc -
EMNLP 2020
Review -
Variance of the Estimator in Machine Learning
Machine Learning -
Some Clustering Papers at ICLR20
Review -
A minimum keystroke (py)Debugger for Lazy ML/DS people who don't IDE
Projects Code -
Recipe for building jq from source without admin(sudo) rights
Code -
The Sigmoid in Regression, Neural Network Activation and LSTM Gates
Machine Learning -
Arithmetic(Book)
Review -
Clean TreeLSTMs implementation in PyTorch using NLTK treepositions and Easy-First Parsing
PyTorch -
Pad pack sequences for Pytorch batch processing with DataLoader
PyTorch -
Modes of Convergence
Misc -
Coordinate Ascent Mean-field Variational Inference (Univariate Gaussian Example)
Bayesian Inference Machine Learning -
Dirichlet Process Gaussian Mixture Models (Generation)
Bayesian Inference -
Gotchas in Cython; Handling numpy arrays in cython class
Code -
Onboarding for Practical Machine Learning Research
Machine Learning -
Equivalence of constrained and unconstrained form for Ridge Regression
Optimization -
Studying drug-drug interactions and predictors of adverse vascular outcomes
Projects -
PyTorch Automatic differentiation for non-scalar variables; Reconstructing the Jacobian
Calculus PyTorch -
From psychologist to CS PhD Student
Work Experiences -
Capturing Last-mile Transactions of Smallholder Palm Oil Farmers
Projects -
Migrating from python 2.7 to python 3 (and maintaining compatibility)
Code -
Lagrange Multipliers and Constrained Optimization
Calculus Optimization -
Taylor Series approximation, newton's method and optimization
Calculus Optimization -
Hessian, second order derivatives, convexity, and saddle points
Calculus -
Jacobian, Chain rule and backpropagation
Calculus Machine Learning -
Gradients, partial derivatives, directional derivatives, and gradient descent
Calculus Machine Learning Optimization -
Derivatives, differentiability and loss functions
Calculus -
Calculus for Machine Learning
Machine Learning Calculus -
Algorithms on Graphs: Fastest Route
Misc -
Gibbs Sampling on Dirichlet Multinomial Naive Bayes (Text)
Bayesian Inference -
Markov Chain Monte-Carlo
Bayesian Inference -
EM Algorithm for Gaussian mixtures
Bayesian Inference -
Communicating Data Science
Work Experiences -
Cross disciplinary projects
Work Experiences -
Conjugate Priors
Bayesian Inference -
Closed form Bayesian Inference for Binomial distributions
Bayesian Inference -
DSO Advice
Work Experiences
subscribe via RSS