semvec/pypi-packages huggingface dataset:
featman 0.1.5
A built up feature tool. Used to make everything simipler

# Featman
Features and sh*t. Use as an abstraction to `Spaceman`. It can be used with the storage layers spaceman provides.

```python
from featman import Features

features = (
    Features(host="localhost", db="global")
        .set_storage("...")
        .set_type("...")
        .set_time(now=False, back=True, month=0, day=0, hour=0, minute=30)
        .set_data(dataframe: pd.Dataframe, time_index=True, scale="minute")
        .set_data(dataframe: pd.Dataframe, time_index=True, scale="minute")
        .set_data(dataframe: pd.Dataframe, time_index=True, scale="minute")
        .set_data(dataframe: pd.Dataframe, time_index=True, scale="minute")
        .push()
)
```
mlvajra 0.1.4.3
A Last weapon to save Data scientist

# mlVajra 
A framework or best practices to develop end to end machine learning pipeline (also has some tips for ML-management people )
Aim :
    To built robust depoyment pipeline strategies using Open source stack
    planning to add as many strategies in this repo pertaining to ML-deployment

## Installation :

`pip install mlvajra` - only installs mlvajra binaries

To install complete dependencies: (for time being)

git clone https://github.com/rajagurunath/mlvajra.git

```
create virtualenv

virtualenv -p python3 vajra_env

source vajra_env\bin\activate

cd mlvajra
Install all required dependencies from repo

pip install -r requirements.txt

```

## TODO list
### Deploy
- Mlflow
- Tensorflow serving

### model-Training /distribuited
- mlflow -generic classification metrics (done)
- nnictl-automl -tensorflow /pytorch 

### Feature Engineering
- pandas
- pyspark-Flint

### preprocessing
- cyclic features (done)
- lag features
- window features