Mlprimitives

New Features

* Publish the pipelines as an `entry_point`
[Issue 175](https://github.com/MLBazaar/MLPrimitives/issues/175) by csala

Primitive Improvements

* Improve pandas.DataFrame.resample primitive [Issue 177](https://github.com/MLBazaar/MLPrimitives/issues/177) by csala
* Improve `feature_extractor` primitives [Issue 183](https://github.com/MLBazaar/MLPrimitives/issues/183) by csala
* Improve `find_anomalies` primitive [Issue 180](https://github.com/MLBazaar/MLPrimitives/issues/180) by AlexanderGeiger

Bug Fixes

* Typo in the primitive keras.Sequential.LSTMTimeSeriesRegressor [Issue 176](https://github.com/MLBazaar/MLPrimitives/issues/176) by DanielCalvoCerezo

New Features

* Add function to run primitives without a pipeline [Issue 43](https://github.com/MLBazaar/MLPrimitives/issues/43) by csala

New Pipelines

* Add pipelines for all the MLBlocks examples [Issue 162](https://github.com/MLBazaar/MLPrimitives/issues/162) by csala

Primitive Improvements

* Add Early Stopping to `keras.Sequential.LSTMTimeSeriesRegressor` primitive [Issue 156](https://github.com/MLBazaar/MLPrimitives/issues/156) by csala
* Make FeatureExtractor primitives accept Numpy arrays [Issue 165](https://github.com/MLBazaar/MLPrimitives/issues/165) by csala
* Add window size and pruning to the `timeseries_anomalies.find_anomalies` primitive [Issue 160](https://github.com/MLBazaar/MLPrimitives/issues/160) by csala

New Features

* Add a single table binary classification dataset [Issue 141](https://github.com/MLBazaar/MLPrimitives/issues/141) by csala

New Primitives

* Add Multilayer Perceptron (MLP) primitive for binary classification [Issue 140](https://github.com/MLBazaar/MLPrimitives/issues/140) by Hector-hedb12
* Add primitive for Sequence classification with LSTM [Issue 150](https://github.com/MLBazaar/MLPrimitives/issues/150) by Hector-hedb12
* Add VGG-like convnet primitive [Issue 149](https://github.com/MLBazaar/MLPrimitives/issues/149) by Hector-hedb12
* Add Multilayer Perceptron (MLP) primitive for multi-class softmax classification [Issue 139](https://github.com/MLBazaar/MLPrimitives/issues/139) by Hector-hedb12
* Add primitive to count feature matrix columns [Issue 146](https://github.com/MLBazaar/MLPrimitives/issues/146) by csala

Primitive Improvements

* Add additional fit and predict arguments to keras.Sequential [Issue 161](https://github.com/MLBazaar/MLPrimitives/issues/161) by csala
* Add suport for keras.Sequential Callbacks [Issue 159](https://github.com/MLBazaar/MLPrimitives/issues/159) by csala
* Add fixed hyperparam to control keras.Sequential verbosity [Issue 143](https://github.com/MLBazaar/MLPrimitives/issues/143) by csala

New Primitives

* mlprimitives.custom.timeseries_preprocessing.time_segments_average - [Issue 137](https://github.com/MLBazaar/MLPrimitives/issues/137)

New Features

* Add target_index output in timseries_preprocessing.rolling_window_sequences - [Issue 136](https://github.com/MLBazaar/MLPrimitives/issues/136)

General Improvements

* Validate JSON format in `make lint` - [Issue 133](https://github.com/MLBazaar/MLPrimitives/issues/133)
* Add demo datasets - [Issue 131](https://github.com/MLBazaar/MLPrimitives/issues/131)
* Improve featuretools.dfs primitive - [Issue 127](https://github.com/MLBazaar/MLPrimitives/issues/127)

New Primitives

* pandas.DataFrame.resample - [Issue 123](https://github.com/MLBazaar/MLPrimitives/issues/123)
* pandas.DataFrame.unstack - [Issue 124](https://github.com/MLBazaar/MLPrimitives/issues/124)
* featuretools.EntitySet.add_relationship - [Issue 126](https://github.com/MLBazaar/MLPrimitives/issues/126)
* featuretools.EntitySet.entity_from_dataframe - [Issue 126](https://github.com/MLBazaar/MLPrimitives/issues/126)

Bug Fixes

* Bug in timeseries_anomalies.py - [Issue 119](https://github.com/MLBazaar/MLPrimitives/issues/119)

General Improvements

* Add Contributing Documentation
* Remove upper bound in pandas version given new release of `featuretools` v0.6.1
* Improve LSTMTimeSeriesRegressor hyperparameters

New Primitives

* mlprimitives.candidates.dsp.SpectralMask
* mlprimitives.custom.timeseries_anomalies.find_anomalies
* mlprimitives.custom.timeseries_anomalies.regression_errors
* mlprimitives.custom.timeseries_preprocessing.rolling_window_sequences
* mlprimitives.custom.timeseries_preprocessing.time_segments_average
* sklearn.linear_model.ElasticNet
* sklearn.linear_model.Lars
* sklearn.linear_model.Lasso
* sklearn.linear_model.MultiTaskLasso
* sklearn.linear_model.Ridge