Skip to content
rraushan
Overview
Initializing search
Home
ML
Maths
ML Sys Design
Guides
rraushan
Home
ML
ML
Overview
Applied Ml
Applied Ml
Communication Primitives
Data Parallelism (DDP)
Exploding / Vanishing Gradients
Floating Point Representation
FSDP / ZeRO
Gradient Accumulation
Gradient Checkpointing
Gradient Clipping
JAX vs PyTorch vs TensorFlow
JIT Compilation
Mixed Precision Training
Numerical Precision Tricks
Pipeline Parallelism
Profiling
Tensor Parallelism
General Ml
General Ml
Activation Functions
Adam / AdamW / Adagrad
Autoencoders
Backpropagation
Bagging
BatchNorm / LayerNorm / RMSNorm
Bayes Theorem
Bias–Variance Tradeoff
Boosting
Clustering (k-means and friends)
CNNs
Confidence Intervals
Convex Functions
Cross Validation
Curse of Dimensionality
Data Whitening
Decision Trees
Dimensionality Reduction
Domain Adaptation
Early Stopping
Ensembles
Entropy
Expectation
Few-Shot / Zero-Shot Learning
Gradient Descent / SGD
Gumbel-Softmax
Jensen–Shannon Divergence
KL Divergence
K-Nearest Neighbours
Linear Regression
Loss Functions
MLE vs MAP
Newton's Method
No Free Lunch Theorem
Overfitting / Underfitting
PDF / PMF
Precision / Recall / F1 / AUC-ROC
Regularisation Methods
RNNs / LSTMs
S4 / State Space Models
Second Order Methods
SVMs
Transfer Learning
Unsupervised vs Supervised
Variance and Covariance
Weight Initialisation
Generative
Generative
Classifier-Free Guidance
Diffusion: Forward Process
Diffusion: Reverse Process (DDPM / DDIM)
Diffusion as SDEs
Flow Matching
GANs
The Score Function
VAEs and the ELBO
ML Notes
Llms
Llms
Causal Attention
Cross Attention
Decoding Techniques
Finetuning
Flash Attention
Griffin
The 1/√d Attention Scaling Factor
Transformer vs RNN vs S4
LoRA
Mixture of Experts
Perceiver
Pretraining
Relative Positional Embeddings
RLHF
RoPE — Rotary Position Embeddings
Scaling Laws
Sinusoidal Embeddings
Tokenisation
Transformer-XL
Maths
Maths
Overview
Linear Algebra
Linear Algebra
Determinant
Dot Product
Eigenvectors and Eigenvalues
Hessian
Jacobian
Linear Independence
Inverse of a Matrix
Null Space and Image Space
Orthogonality
Positive Semi-Definite Matrices
Rank and Span
Singular Matrices
ML Sys Design
ML Sys Design
Overview
FB News Feed Ranking — ML System Design Master Notes
Deep Neural Networks for YouTube Recommendations — Master Notes
Guides
Guides
Overview
Python Typing
UV for Python
Weight Initialization in DL
Maths Notes
¶
Notes on Mathematics — linear algebra, calculus, probability, statistics, and more.
Back to top