The fundamental package for scientific computing with Python
D&I Grant from CZI
Including NumPy, SciPy, Matplotlib and Pandas

Powerful N-dimensional arrays
Fast and versatile, the NumPy vectorization, indexing, and broadcasting concepts are the de-facto standards of array computing today.

Numerical computing tools
NumPy offers comprehensive mathematical functions, random number generators, linear algebra routines, Fourier transforms, and more.

NumPy supports a wide range of hardware and computing platforms, and plays well with distributed, GPU, and sparse array libraries.

The core of NumPy is well-optimized C code. Enjoy the flexibility of Python with the speed of compiled code.

Easy to use
NumPy’s high level syntax makes it accessible and productive for programmers from any background or experience level.

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Cheap Wholesale Online Shop UK CNMJI Decor Windfahne Wetterfahne Halterung Garten Yard Dekorati safety Sinfonien 5+7 CNMJI Decor Windfahne Wetterfahne Halterung Garten Yard Dekorati Some reservation Produktbeschreibungen Produktbeschreibungen Classica Orchestrale - BEETHOVEN Ludwig van: Symphonies; Sinfonia n.5 op 67 in do (1807); Sinfonia n.7 op 92 in LA (1812) Rezension The Pittsburgh/Honeck Beethoven album reaches the shortlist of this century's great Beethoven symphony recordings. Also on my list are recordings by the Leipzig Gewandhaus with Riccardo Chailly, the Berlin Philharmonic with Claudio Abbado, and Anima Eterna with Jos van Immerseel. This disc might have the best sound quality of all and it certainly has revolutionary booklet notes. You don't often find yourself learning new things, and hearing new angles, in music as well-worn as Beethoven's Fifth. That is what makes this such a special experience. RECORDING OF THE MONTH --MusicWeb, Nov'15Sensible readers will already possess Carlos Kleiber's legendary coupling of Beethoven 5 and 7, taped with the Vienna Philharmonic in the mid 1970s. Manfred Honeck's Pittsburgh disc will hopefully turn out to be as enduring. Honeck spent many years as Vienna Philharmonic violinist, playing Beethoven under the likes of Karajan, Abbado, Harnoncourt and Kleiber, so you'd expect him to know these pieces inside out. These performances, though never sluggish, are huge. In the best possible way. Their grandeur is irresistible, reminding us just how rare large-scale, modern instrument performances are. We know that Beethoven preferred big orchestras. He'd presumably have loved this disc. Antiphonal violins are beautifully clear, and the lower strings possess incredible depth. Winds and brass are outstanding, with spectacular horns. The weighty, rhetorical opening of Honeck's Fifth is striking, in his words giving it a grandiose weight, power and vehemence. What ensues has intoxicating energy. Honeck's notes point out various things which usually pass unheard, like the horns blasting out the motto theme six minutes in. Taut inner movements and a very Brucknerian transition lead to the most exultant of finales. Glorious. As is this Seventh, the Vivace's rhythms enunciated with impeccable clarity. Honeck follows Carlos Kleiber in having the violins play pizzicato at the end of the second movement, a decision based on Kleiber's father's examination of Beethoven's manuscript. And, again, what a finale. The earth moves. There's a wonderful moment seven minutes in, where the shadows briefly descend. Honeck's handling of it is matchless, and the closing pages are overwhelming. This disc should be prescribed as an anti-depressant, showing doubters exactly why classical music can still entertain and overwhelm. Everything I've heard from this particular orchestra/conductor combo has delighted me, and this is their best recording to date. Flawless engineering, and Honeck's enthusiastic notes are a joy to read. CHOSEN AS ONE OF THE BEST CLASSICAL CDS OF 2015 --ArtsDesk 05/12/15A shining example of a conductor who understands the works from inside out. **** Musical Opinion, July-Sept'16. /// The Pittsburg playing marries epic power with a revealing translucency of texture. Honeck has a wonderful ear for detail. GRAMOPHONE EDITORS CHOICE --Gramophone, Dec'15 Gerade die in unzähligen Variationen buchstäblich überhörten Symphonie-Klassiker von Beethoven in dieser brillanten Aufnahme zu erleben, ist eine Wiederentdeckung. Jede Nuance, jedes Detail, auch jedes laute Atmen der Musiker wurde von fünf omnidirektiona Musik-CDs Vinyl => Klassik => Konzerte, Sinfonien Orchesterm you can then use our order tracking system to track the status of your order. we even offer a text messaging service; just fill in your mobile details when you order - it's that easy!
Open source
Distributed under a liberal BSD license, NumPy is developed and maintained publicly on GitHub by a vibrant, responsive, and diverse community.

Try NumPy
Enable the interactive shell

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Live in Japan 97 by Ash Ra Tempel (1998-10-13) 100% High Quality Guarantee if we were to recommend something due to bias or laziness, readers wouldn't support our work. Cheap Wholesale Online Shop UK CNMJI Decor Windfahne Wetterfahne Halterung Garten Yard Dekorati safety Musik-CDs Vinyl => Featured Categories => Live-Alben CNMJI Decor Windfahne Wetterfahne Halterung Garten Yard Dekorati

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CNMJI Decor Windfahne Wetterfahne Halterung Garten Yard Dekorati

  • Diese schöne Wetterfahne wurde aus Edelstahlmaterialien hergestellt und lackiert, um Ihrem Garten dauerhafte Farbe zu verleihen, einfach zu montieren und langlebig.
  • Praktische Werkzeuge, der architektonische Stil, die Wetterfahne ist nicht nur sehr schön, sondern auch sehr nützlich für die Überwachung der Windrichtung. Sehr gut für die Außendekoration geeignet. Mit exquisitem Formdesign, das es attraktiver macht, werden Ihre Besucher Ihr Zuhause sicherlich bald finden. Und es kann gut Ihren Garten schmücken. Überraschen Sie sie!
  • Unser einzigartiges Punktkontaktdesign ermöglicht es unseren Leitschaufeln, sich leicht im Wind zu drehen. Diese Art von Wetterfahne ist nicht nur schön, sondern es ist auch nützlich zu wissen, in welche Richtung der Wind weht.
  • Die Halterung kann auf horizontalen und vertikalen Flächen installiert werden. Setzen Sie die Metallstatue einfach in den Boden oder die Decke ein, um die Installation abzuschließen. Lassen Sie die Wetterfahne Ihre Position schützen und zeigen Sie anderen die Richtung der Windgeschwindigkeit.
  • Schöne Figur, geeignet für Ihre Haus- und Gartendekoration, aber auch eine wunderbare Dekoration für die Terrassendekoration. Ideal für Gärten, Häuser, Gartenhäuser, Zäune, Pergolen, Gewächshäuser, Gewächshäuser, Scheunen oder Pavillons. Zeigt die Richtung der Windgeschwindigkeit an.


Die Wetterfahne ist ein attraktives Element im Garten und hat die ideale Größe für die Montage an Schuppen, Zaunpfählen, Pavillons, Garagen und kleinen Häusern. Es ist wirklich einfach zu montieren und wird mit einem universellen Montagesatz geliefert, der für die meisten Anwendungen geeignet ist. Die gute Sichtbarkeit dieser Metallwetterfahne mit schwarzer Pulverbeschichtung zeigt Ihnen viele Jahre lang, woher der Wind kommt.

1. Architektonischer Stil. Diese Art von Wetterfahne ist nicht nur schön, sondern auch nützlich, um zu wissen, in welche Richtung der Wind weht.
2. Eine sehr starke Wetterfahne. Es wird auf Ihrem Schuppen, auf dem Dach oder auf den perfekten Hochzeits- und Geburtstagsgeschenken großartig aussehen.
3. Dekorative Wetterfahne. Eine Wetterfahne dieser Größe ist perfekt für Ihr Haus, Garage, Kuppel, Scheune oder Pavillon.
4. Produktgröße: Gesamthöhe 35*50 CM.

Lieferumfang: 1 * Gartenpfosten

  • Nearly every scientist working in Python draws on the power of NumPy.

    NumPy brings the computational power of languages like C and Fortran to Python, a language much easier to learn and use. With this power comes simplicity: a solution in NumPy is often clear and elegant.

    Quantum Computing Statistical Computing Signal Processing Image Processing Graphs and Networks Astronomy Processes Cognitive Psychology
    QuTiP Pandas SciPy Scikit-image NetworkX AstroPy PsychoPy
    PyQuil statsmodels PyWavelets OpenCV graph-tool SunPy
    Qiskit Xarray python-control Mahotas igraph SpacePy
    Seaborn PyGSP
    Bioinformatics Bayesian Inference Mathematical Analysis Chemistry Geoscience Geographic Processing Architecture & Engineering
    BioPython PyStan SciPy Cantera Pangeo Shapely COMPAS
    Scikit-Bio PyMC3 SymPy MDAnalysis Simpeg GeoPandas City Energy Analyst
    PyEnsembl ArviZ cvxpy RDKit ObsPy Folium Sverchok
    ETE emcee FEniCS Fatiando a Terra
  • NumPy's API is the starting point when libraries are written to exploit innovative hardware, create specialized array types, or add capabilities beyond what NumPy provides.

    Array Library Capabilities & Application areas
    Dask Distributed arrays and advanced parallelism for analytics, enabling performance at scale.
    CuPy NumPy-compatible array library for GPU-accelerated computing with Python.
    JAX Composable transformations of NumPy programs: differentiate, vectorize, just-in-time compilation to GPU/TPU.
    Xarray Labeled, indexed multi-dimensional arrays for advanced analytics and visualization
    Sparse NumPy-compatible sparse array library that integrates with Dask and SciPy's sparse linear algebra.
    PyTorch Deep learning framework that accelerates the path from research prototyping to production deployment.
    TensorFlow An end-to-end platform for machine learning to easily build and deploy ML powered applications.
    MXNet Deep learning framework suited for flexible research prototyping and production.
    Arrow A cross-language development platform for columnar in-memory data and analytics.
    xtensor Multi-dimensional arrays with broadcasting and lazy computing for numerical analysis.
    XND Develop libraries for array computing, recreating NumPy's foundational concepts.
    uarray Python backend system that decouples API from implementation; unumpy provides a NumPy API.
    tensorly Tensor learning, algebra and backends to seamlessly use NumPy, MXNet, PyTorch, TensorFlow or CuPy.
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    NumPy lies at the core of a rich ecosystem of data science libraries. A typical exploratory data science workflow might look like:

    For high data volumes, Dask and Ray are designed to scale. Stable deployments rely on data versioning (DVC), experiment tracking (MLFlow), and workflow automation (Airflow and Prefect).

  • NumPy forms the basis of powerful machine learning libraries like scikit-learn and SciPy. As machine learning grows, so does the list of libraries built on NumPy. TensorFlow’s deep learning capabilities have broad applications — among them speech and image recognition, text-based applications, time-series analysis, and video detection. PyTorch, another deep learning library, is popular among researchers in computer vision and natural language processing. MXNet is another AI package, providing blueprints and templates for deep learning.

    Statistical techniques called ensemble methods such as binning, bagging, stacking, and boosting are among the ML algorithms implemented by tools such as XGBoost, LightGBM, and CatBoost — one of the fastest inference engines. Yellowbrick and Eli5 offer machine learning visualizations.

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    NumPy is an essential component in the burgeoning Python visualization landscape, which includes Matplotlib, Seaborn, Plotly, Altair, Bokeh, Holoviz, Vispy, Napari, and PyVista, to name a few.

    NumPy’s accelerated processing of large arrays allows researchers to visualize datasets far larger than native Python could handle.