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CAFA 5 Protein Function Prediction
Child Mind Institute - Detect Sleep States
CommonLit - Evaluate Student Summaries
G-Research Crypto Forecasting
Google - Fast or Slow? Predict AI Model Runtime
Google QUEST Q&A Labeling
ICR - Identifying Age-Related Conditions
LANL Earthquake Prediction
Linking Writing Processes to Writing Quality
Mechanisms of Action (MoA) Prediction
MLB Player Digital Engagement Forecasting
NeurIPS 2023 - Machine Unlearning
Novozymes Enzyme Stability Prediction
Open Problems – Single-Cell Perturbations
RSNA 2023 Abdominal Trauma Detection
Stanford Ribonanza RNA Folding
Tweet Sentiment Extraction
UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN)
Vesuvius Challenge - Ink Detection
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categorical cross entropy
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substring segmentation
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adversarial validation
ALiBi positional encoding
BPE tokenizer
Online hard negative mining
Sequence bucketing
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KS statistic
Lasso Regression
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Multiple Instance Learning
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overfitting yourself
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thresholding
triplet mining
voice activity detection (VAD)
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binary classification
classification
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machine translation
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ordering objects in list
regression
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signal processing
speech to Text (STT)
Time Series
transcription
Unknown Class Classification
techniques
code quality
encapsulate team's code in class
cross validation
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select 2 best models for each fold on CV
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identifying slow feature generation
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Add noise to denoise median statistic
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create features through the ratio between different features
data period selection
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distribution matching
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drop redundant columns
extract features using NLP on academic papers
Fibonacci window lag
filling training data (impute data)
frequency encoding
Identify poor data sources
is present bit
Leave-one-out encoding
normalize features
one-hot encoding
permutation feature importance to select features
placeholder for invalid values
reduce resolution
sliding window
Spectrogram dithering
subtraction to avoid dependence on mean
target encoding
text data cleaning
thermometer encoding
Training own Tokenizer
Transformer to compress dimensions rather than flattening
formulas
entropy
variance
kaggle-only-techniques
How to understand your place on an overfitted Leaderboard
leaderboard probing
models
add signal to attention bias
create enriching features first, then mix across time
expert models
Freezing Layers
Gradient-Boosted Decision Tree
GRU head (neck) after the backbone layer
kenlm
RAPIDS SVR
Stochastic Weights Averaging
Train on external data first
regularization
adding epsilon to regularize
DropEdge
dropout
label smoothing
weight decay
target
binary encoded categorical ordinal targets
clip outputs to be within range
custom labels
derive results from logits
downsample and upsample output
drop bad targets from CV
hardness to predict label
ignore edge of output prediction
percentile thresholding
postprocess to match target distribution
pseudo-labeling
remove stray pixels
target scaling
time since an event occurred as an auxiliary target
use intermediate layer results (weighted)
custom loss
remove easy examples
remove rows where feat=x to find unknown data clusters
remove test data leakage
Rotational positional embedding
sanity check
xpos positional encoding
tools
Demucs
ftfy
Numba
polars
Ray Tune
runpod.io
thefuzz (prev fuzzywuzzy)
vast.ai
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is present bit
is present bit
May 08, 2024, 1 min read
a boolean column that tells you if values exist or not in this column
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MLB Player Digital Engagement Forecasting