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## Presentations

(117)## Documents

(2)## Likes

(3)### How deep generative models can help quants reduce the risk of overfitting?

Gautier Marti
•
3 years ago

### 2019 GDRR: Blockchain Data Analytics - QuTrack: Model Life Cycle Management for AI and ML models using a Blockchain approach - Srikanth Krishnamurthy, October 7, 2019

The Statistical and Applied Mathematical Sciences Institute
•
4 years ago

### AutoML lectures (ACDL 2019)

Joaquin Vanschoren
•
4 years ago

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Tags

quantuniversity
machine learning
ai
qusandbox
analytics
deep learning
fintech
model risk
qwafafew
data science
python
r
time series
model validation
synthetic data
keras
neural networks
anomaly detection
big data
finance
blockchain
apache spark
stress testing
gan
nlp
tensorflow
credit risk
docker
matlab
clustering
fraud
algorithms
model risk management
machinelearning
qusynthesize
econometrics
bitcoin
prmia
roboadvisors
rnn
gpu
theano
feature engineering
pca
aws
regression
anomaly
outlier
cloud
data
ai risk
eu ai
medical diagnosis
acne
cfa python data science
responsible ai
auditing
credit decision making
algorithmic auditing
quantum computing
explainable ai
ethics
alternative data
portfolio optimization
asset management
modelgovernance
modelrisk
quacademy
mlm
quresearchhub
qumodelstudio
qutrack
dask
rapids
nvidia
cfa
disrupt19
optimization
framework
webinar
stationarity
arima
lstm
model governance
automl
day2
crash course
replicability
reproducibility
northfield
northeastern university
mathworks
risk management
cryptocurrencies
cryptocurrency
dlt
arpm
regtech
sandbox
quant models
quantitative finance
chicago
odsc
bigdl
databricks
autoencoder
cnn
tsne
gower
lending club
missing data
imputation
deletion
knn
decision trees
predictive analytics
azure
spark
hyperloglog
outlier analysis
energy
model verification
quantifying uncertainty
dodd-frank
dimensionality
policy

See more