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Best Manufacturers Inc., a family business, has designed and fabricated the highest quality, most sanitary professional whisks and mashers in Portland, Oregon since 1959. With roots in the restaurant supply industry, Best supplies the same durable cooking tools required by the rigors of the professional kitchen to the home cook. Best Whips are also manufactured to the sanitary specifications of the National Sanitation Foundation (NSF), the recognized authority in professional kitchen tools and kitchen equipment. As a third generation specialty manufacturer/distributor, Best is proud to offer a large selection of Made in America products as well as products from Mexico, Germany and China. Distributed products are selected with the same professional standard, consistent with our reputation as a manufacturer of fine kitchen tools.
This durable 12-inch flat roux whip provides easy access to the good stuff on a pan's bottom and corners, which translates into more flavorful gravies. Its flat 4-wire design is also great for mixing roux--the butter and flour mixture used in thickening sauces--and stiff batters, or use it to deglaze. The high-tensile stainless-steel wire is rustproof and epoxy sealed for sanitation, and the handle is weighted to give you better mixing control and comfort. Best of all, the whip, including its lovely red lacquered birch wood handle, is dishwasher-safe. "i"--Doree Armstrong
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.
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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.|
NumPy lies at the core of a rich ecosystem of data science libraries. A typical exploratory data science workflow might look like:
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. AFFY Round Cut White Natural Diamond Contour Band Ring in 14K So is another AI package, providing blueprints and templates for deep learning.
NumPy is an essential component in the burgeoning 14k Rose Gold Morganite and 0.2 Dwt Diamond Earrings Jewelry Gif, which includes Matplotlib, Seaborn, Plotly, Marky G Apparel Girls' Big Sportswear Fine Jersey Longer Length, Bokeh, Holoviz, Vispy, Napari, and Boao Christmas Stocking Holder Metal Hook Hanger Christmas Safet, to name a few.
NumPy’s accelerated processing of large arrays allows researchers to visualize datasets far larger than native Python could handle.