CHE COSA SI METTE NEL COLOPHON DI UN LIBRO? ✍🏻
#scrittura#writingtips
⏩ Il termine colophon deriva dal greco kolophón che significa "cima", è la pagina che in genere troviamo all'inizio di un libro a sinistra. Tutti i volumi (anche gli e-book) devono obbligatoriamente inserirla con i seguenti dati:
✅ la data di pubblicazione del libro,
✅ il copyright cioè chi ha i diritti dell'opera (nella maggior parte dei casi l'editore, oppure l'autore),
✅ l'ISBN, international serial book number che identifica il prodotto libro, l'editore, il Paese,
✅ il titolo dell'opera, traduttori, illustratori, fotografi, grafici, editor,
✅ in caso di ristampa o di nuova edizione, vanno riportate complete (indicando mese e anno) la data della prima edizione e la data dell'ultima,
✅ i dati dello stampatore possono esser inseriti nel colophon ma spesso sono indicati nell'ultima pagina (sono obbligatori).
@writingway
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http://scikit-learn.org/stable/
scikit-learn
#Machine#Learning in Python
Simple and efficient tools for data mining and data analysis
Accessible to everybody, and reusable in various contexts
Built on #NumPy, #SciPy, and #matplotlib
Open source, commercially usable - BSD license
http://scitools.org.uk/iris/docs/latest/userguide/index.html
Iris seeks to provide a powerful, easy to use, and community-driven Python library for analysing and visualising #meteorological and #oceanographic data sets.
With Iris you can:
Use a single #API to work on your data, irrespective of its original format.
Read and write (CF-)netCDF, GRIB, and PP files.
Easily produce graphs and maps via integration with #matplotlib and #cartopy.
http://scitools.org.uk/cartopy/docs/latest/index.html
Cartopy is a Python package designed to make drawing maps for data analysis and visualisation as easy as possible.
#Cartopy makes use of the powerful #PROJ.4, #numpy and #shapely libraries and has a simple and intuitive drawing interface to #matplotlib for creating publication quality maps.
Some of the key features of cartopy are:
object oriented projection definitions
point, line, vector, polygon and image transformations between projections
integration to expose advanced mapping in matplotlib with a simple and intuitive interface
powerful vector data handling by integrating shapefile reading with Shapely capabilities
http://matplotlib.org/
#matplotlib is a python #2D#plotting library which produces publication quality figures in a variety of hardcopy formats and interactive environments across platforms. matplotlib can be used in #python scripts, the python and #ipython shell (ala MATLAB®* or Mathematica®†), web application servers, and six #graphical user interface toolkits.
screenshots
http://devarea.com/machine-learning-with-python-introduction/#.Whs6iCehU8o
#Machine_Learning With Python – Introduction
#Numpy is package for multi dimension arrays – very effective implementation
#Scipy – package for scientific programming , mathematics , signal processing and more
#Pandas – package for data handling
#Matplotlib – package for data visualization (graphs)
#Seaborn – extend Matplotlib with statistical graphs
#Scikits – many extensions to spicy for specific fields like x-ray, image processing , deep learning and many more