Implements tic-tac-toe game to play on console, either with human or AI players.
  Various levels of AI players are trained through the Q-learning algorithm.

Code execution timing functions 'tic' and 'toc' that
    can be nested. One can record all timings while a complex script is
    running, and examine the values later. It is also possible to instrument
    the timing calls with custom callbacks. In addition, this package provides
    class 'Stack', implemented as a vector, and class 'StackList', which is a
    stack implemented as a
    list, both of which support operations 'push', 'pop', 'first_element',
    'last_element' and 'clear'.

Tidal analysis of evenly spaced observed time series (time step 1 to 60 min) with or
    without shorter gaps using the harmonic representation of inequalities.
    The analysis should preferably cover an observation period of at least 19 years.
    For shorter periods low frequency constituents are not taken into account, in accordance with the Rayleigh-Criterion.
    The main objective of this package is to synthesize or predict a tidal time series.

Implements harmonic analysis of tidal and sea-level data.
  Over 400 harmonic tidal constituents can be estimated, all with 
  daily nodal corrections. Time-varying mean sea-levels can also
  be used.

Calculate Characteristics of Quasi-Periodic Time Series, e.g. Estuarine Water Levels.

Tide analysis and prediction of predominantly semi-diurnal tides
    with two high waters and two low waters during one lunar day (~24.842 hours,
    ~1.035 days). The analysis should preferably cover an observation period of at
    least 19 years. For shorter periods, for example, the nodal cycle can not be
    taken into account, which particularly affects the height calculation. The main
    objective of this package is to produce tide tables.

Provides 'Apache Spark' style window aggregation for R dataframes and remote 'dbplyr' tables via 'mutate' in 'dplyr' flavour.

The goal of this package will be to provide a simple interface for automatic machine learning that fits the 'tidymodels' framework. The intention is to work for regression and classification problems with a simple verb framework.