Study notes
os
path
sfile()
join()
listdi()
sort()
makedirs()
walk()
glob
glob()
shutil
copy()
rmtree()
pandas
read_csv()
to_csv()
plot
bar()
sample()
to_csv()
[COLUMN _NAME/ QUERT_RESULT].value_counts()
COLUMN _NAME.unique()
[COUMN1_NAME, ....COLUMNn_NAME].describe()
to_dict()
numpysqrt()
polyfit()
poly1d
float()
average()
genfromtxt)_
matplotlib
pyplot
show
plot
bar()
subplots()
scatter()
xlabel()
ylabel()
title()
imshow()
image
imread()
figure()
gca()
set_title
set_xlabel()
set_ylabel()
sklearn
fit(data)
transform()
fit-transform
esemble
RandomForestRegressor()
GradientBoostingRegressor()
RandomForestClassifier()
tree
DecisionTreeRegressor().fit()
export_text(<MODEL>)
model_selection
train_test_split()
liniar_model
LiniarRegression().fit()
Lasso().fit()
Ridge().fit()
GreadSearchCV
<ANY MODEL>.predict()
liniar_model
LiniarRegression
LogisticRegression()
predict()
predict_proba()
metrics
mean_squared_error
r2_score
make_scorer
accuracy_score
classification_report
precision_score
recall_score
confusion_matrix
roc_curve
roc_auc_score
compose
ColumTransformer
decomposition
PCA
cluster
AgglomerativeClustering
KMeans
Kmeans.fit_predict()
<ANY CLUSTERING MODEL??>.fit_predict()
pipeline
Pipeline()
publish()
publish_pipeline()
impute
SimpleImputer
preprocessing
StandardScaler
OneHotEncoder
MinMaxScaler
joblib
dump()
load()
torch
max()
sum()
ndim
shape
dtype
rand
zero
ones
arange (range - deprecated)
loss_criteria
item()
backward()
nn
Module
Linear
CrossEntropyLoss
Sequential
CenterCrop
Normalize
Conv2d
MaxPool2d
Dropout2d
functional
relu
CrossEntropyLoss
utils
data
TensorDataset
DataLoader
random_split()
Tensor()
optimizer
zero_grade()
step()
optim
Adam
cuda
is_available()
torchvision
transforms
Normalize()
datasets
ImageFolder
models
RunDetails
RunDetails()
show()
Experiemet
Experiment()
submit()
get()
run.wait_for_completion()
get_details_with_logs()
get_metrics()
get_runs()
get_portal_url
download_files()
get_details_with_logs()
get_all_logs()
start_logging()
log()
log_list()
log_image
log_row()
upload_file()
complete()
get_file_names
download_files()
get_details_with_logs()
Model
list()
tag()
properties()
deploy()
version()
wait_for_deployment()
state
run()
scoring_uri
delete()
Run
get_context()
register_model()
wait_for_completion()
get_children()
get_output()
AutoMLConfig
AutoMLConfig()
automl_utils
get_primary_metrics()
argparse
ArgumentParser()
add_argument()
parse_args()
reg
Environment
from_conda_specification()
python
conda_dependencies()
get()
inferencing_stack_version()
mlflow
set_tracking_uri()
set_experiment()
start_run()
log_metric()
log_param()
log_artifact()
ComputeTarget
ComputeTarget()
create()
training_cluster.wait_for_completion()
AmlComputeprovisioning_configuration()
ComputeTargetException
Dadastore
register_azure_blob_container()
get()
get_default_datastore()
Dataset
Tabular
from_delimited_files()
File
from_files()
upload_directory()
register()
get_by_name()
get_by_id
to_pandas_dataframe()
as_named_input()
input_datasets()
as_download()
as_named_input()
take()
to_path()
Workspace
from_config()
datasets()
azureml
core
CondaDependencies()
create()
ScriptRunConfig()
DockerConfiguration
DockerConfiguration()
requests
post()
PipelineParameter
PipelineParameter()
ScheduleRecurrence
ScheduleRecurrence()
Schedule
create()
InferenceConfig
InferenceConfig()
AciWebservice
AciWebservice
deploy_configuration()
json
dumps()
loads()
ParallelRunConfig
ParallelRunConfig()
ParallelRunStep
ParallelRunStep()
OutputFileDatasetConfig
OutputFileDatasetConfig()
HyperDriveConfig
HyperDriveConfig()
PrimaryMetricGoal
PrimaryMetricGoal
MAXIMIZE
opendp
smartnoise
core
Analysis()
release()
Dataset()
dp_mean()
MimicExplainer
MimicExplainer()
explain_global()
explain_local()
TabularExplainer
TabularExplainer()
explain_global()
explain_local()
PFIExplainer
PFIExplainer()
explain_global()
explain_local()
ExplanationClient
from_run()
upload_model_explanation()
download_model_explanation()
get_feature_importance_dict()
==
response.json()
loc_auc_score()
fit_transform()
fit()
sample()
head()
tail()
transforms
value_counts()
==
en()
format()
References:
NumPy user guide — NumPy v1.24 Manual
Introduction to Tensors | TensorFlow Core
pandas - Python Data Analysis Library (pydata.org)
All things · Deep Learning (dzlab.github.io)
API reference — pandas 1.5.3 documentation (pydata.org)
Track ML experiments and models with MLflow - Azure Machine Learning | Microsoft Learn