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Karl Lagerfeld Paris Women's Knit Bolero

$28

Karl Lagerfeld Paris Women's Knit Bolero

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Product description

Long sleeve knit cardigan with open front and contrast trim and cuff


From the manufacturer

Karl Lagerfeld Brand LogoKarl Lagerfeld Brand Logo
Karl Lagerfeld ParisKarl Lagerfeld Paris

Tulip Sleeve amp; Cocktail Dresses

Tulip Sleeve Crepe Dress

Tulip Sleeve Crepe Dress

Tweed Dress

Tweed Dress

Chiffon Sleeve Dress

Chiffon Sleeve Dress

Ruffle Sleeve Dress

Ruffle Sleeve Dress

Sheer Sleeve Sheath Dress

Sheer Sleeve Sheath Dress

Features
3/4 Length Sleeve Pearl amp; Chain Detail Chiffon Slit Sleeve Pearl Detail on Sleeve Pearl Sleeve Cuff Detail
Additional Features
Zipper Closure 2 Front Pockets Invisible Back Center Zipper Zipper Closure Center Back Zipper
Shape
Scuba Crepe Sheath Crepe Sheath Scuba Crepe Sheath Sheath
Sizes
0 - 16 0 - 16 0 - 16 0 - 16 0 - 16
Additional Colors

Casual Dresses

Tweed Shift Dress

Tweed Shift Dress

Bell Sleeve Dress

Bell Sleeve Dress

Tweed Shift Dress

Tweed Shift Dress

Ruffle Sleeve Crepe Dress

Ruffle Sleeve Crepe Dress

Belted Tweed Shift Dress

Belted Tweed Shift Dress

Tweed Shift Dress

Tweed Shift Dress

Applique Shift Dress

Applique Shift Dress

Features
2 Front Pockets Pearl Detail on Neck amp; Sleeves Short Sleeve Pearl Detail on Sleeve Includes Chain Belt Scoop Neck Sleeveless 3D Embroidery
Additional Features
Pearl Detail on Pockets 2 Front Pockets Available in Solids amp; Prints 2 Tier Hem 2 Front Pockets Additional Prints Available
Shape
Shift Sheath Shift Sheath Shift Shift Shift
Sizes
0 - 16 0 - 16 0 - 16 0 - 16 0 - 16 0 - 16 0 - 16
Additional Colors

Cardigans, Stoles, amp; Jumpsuits

Tweed Open Front Jacket

Tweed Open Front Jacket

Tweed Open Front Jacket

Tweed Open Front Jacket

Applique Cardigan

Applique Cardigan

Embellished Tulle Stole

Embellished Tulle Stole

Cropped Jumpsuit

Cropped Jumpsuit

Belted Cropped Jumpsuit

Belted Cropped Jumpsuit

Features
Fringe Detail at Neck amp; Sleeve Chain Detail at Hem amp; Cuff Pearl Button Front Embellished Pearl Wrap Side Pocket Detail Side Pocket Detail
Additional Features
3/4 Sleeve Length Available in Solids amp; Prints Self Belt Included
Shape
Cropped Ceopped
Sizes
X-Small - X-Large X-Small - X-Large X-Small - X-Large One Size 0 - 16 0 - 16
Additional Colors

Karl Lagerfeld Paris Women's Knit Bolero

NumPy
The fundamental package for scientific computing with Python
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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.

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

Performant
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.

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
>
  • 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 Chandrakala Women's Stretchable Readymade Indian Ethnic Saree Bl
    Qiskit Xarray python-control Mahotas Bogner Fire + Ice Sassy Down Ski Jacket SpacePy
    Seaborn The Way It Is Explicit Lyrics
    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 Flexicore Packaging | Polka Dot Gift Wrap Tissue Paper | Size: 1 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
    False Eyelashes Mink Natural Look Fluffy Wispy False Lashes Dram 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:

    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 Angel caller Cat Necklaces 925 Sterling Silver Jewelry Cute Doub and SciPy. As machine learning grows, so does the list of libraries built on NumPy. Blown Glass Octopus, Glass Octopus, Glass, Octopus, Ocean, Octop 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, Manhattan Comfort Kari Modern Contemporary Living Room Velvet Ac, 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.