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IPython Notebook(s) demonstrating deep learning functionality.IPython Notebook(s) demonstrating scikit-learn functionality.

machine-learning deep-learning data-science big-data aws tensorflow theano caffe scikit-learn kaggle spark mapreduce hadoop matplotlib pandas numpy scipy kerasThis repository contains the entire Python Data Science Handbook, in the form of (free!) Jupyter notebooks. Run the code using the Jupyter notebooks available in this repository's notebooks directory.

scikit-learn numpy jupyter-notebook matplotlib pandasStop plotting your data - annotate your data and let it visualize itself. HoloViews is an open-source Python library designed to make data analysis and visualization seamless and simple. With HoloViews, you can usually express what you want to do in very few lines of code, letting you focus on what you are trying to explore and convey, not on the process of plotting.

visualization analysis bokeh matplotlib interactive data-science exploratory-data-analysis pandasThis is the list of published articles on medium.com ðŸ‡¬ðŸ‡§, habr.com ðŸ‡·ðŸ‡º, and jqr.com ðŸ‡¨ðŸ‡³. Icons are clickable. Also, links to Kaggle Kernels (in English) are given. This way one can reproduce everything without installing a single package. Assignments will be announced each week. Meanwhile, you can pratice with demo versions. Solutions will be discussed in the upcoming run of the course.

machine-learning data-analysis data-science pandas algorithms numpy scipy matplotlib seaborn plotly scikit-learn kaggle-inclass vowpal-wabbit ipynb docker mathNote: mpld3 is in the process of switching maintainers: feature requests & bug reports are likely to be delayed. If you are interested in contributing to this project, please contact one of the repository owners. This is an interactive D3js-based viewer which brings matplotlib graphics to the browser. Please visit http://mpld3.github.io for documentation and examples.

d3 matplotlibVisual analysis and diagnostic tools to facilitate machine learning model selection. Image by Quatro Cinco, used with permission, Flickr Creative Commons.

machine-learning visual-analysis model-selection visualization scikit-learn visualizer matplotlib estimator residuals transformer advantage anacondaRetrieve, construct, analyze, and visualize street networks from OpenStreetMap: full overview. You can just as easily download and work with building footprints, elevation data, street bearings/orientations, and network routing.

openstreetmap gis network street-networks shapefile visualization graph overpass-api graphs networkx matplotlib spatial-analysis geospatial maps urban-planning design transportation physics math geographyCartopy is a Python package designed to make drawing maps for data analysis and visualisation easy. Documentation can be found at https://scitools.org.uk/cartopy/docs/latest/.

maps geometry spatial matplotlib projections cartopyOfficial Matplotlib cheat sheets

cheatsheet matplotlibLeveraging the Jupyter interactive widgets framework, ipympl enables the interactive features of matplotlib in the Jupyter notebook and in JupyterLab. Besides, the figure canvas element is a proper Jupyter interactive widget which can be positioned in interactive widget layouts.

interactive matplotlib jupyterlab-extension jupyter jupyterlab widgetsThis repository, matplotlib/mplfinance, contains a new matplotlib finance API that makes it easier to create financial plots. It interfaces nicely with Pandas DataFrames. More importantly, the new API automatically does the extra matplotlib work that the user previously had to do "manually" with the old API. (The old API is still available within this package; see below).

finance market-data matplotlib candlestick candlestick-chart ohlc intraday-data ohlcv ohlc-chart ohlc-plot mplfinance trading-days ohlc-data candlestickchartThis project showcases how you can use fastpages to create a static dashboard that update regularly using Jupyter Notebooks. Using fastpages, data professionals can share dashboards (that are updated with new data automatically) without requiring any expertise in front end development. The content of this site shows statistics and reports regarding Covid-19.

github-pages data-science jupyter analytics nteract data-visualisation matplotlib pymc3 fastai altair papermill github-actions covid-19 covid19 covid-data fastpagesAll code and material is licensed under a Creative Commons Attribution-ShareAlike 4.0. You can test your installation before the tutorial using the check-installation.py script.

matplotlib tutorialPractice and tutorial-style notebooks covering wide variety of machine learning techniques

numpy statistics pandas matplotlib regression scikit-learn classification principal-component-analysis clustering decision-trees random-forest dimensionality-reduction neural-network deep-learning artificial-intelligence data-science machine-learning k-nearest-neighbours naive-bayesA comprehensive list of Deep Learning / Artificial Intelligence and Machine Learning tutorials - rapidly expanding into areas of AI/Deep Learning / Machine Vision / NLP and industry specific areas such as Climate / Energy, Automotives, Retail, Pharma, Medicine, Healthcare, Policy, Ethics and more.

machine-learning deep-learning tensorflow pytorch keras matplotlib aws kaggle pandas scikit-learn torch artificial-intelligence neural-network convolutional-neural-networks tensorflow-tutorials python-data ipython-notebook capsule-networkfor native inclusion into LaTeX documents. matplotlib2tikz works with both Python 2 and Python 3.

tikz matplotlib pgfplots latexProfilers are extremely helpful tools. They help us dig deep into code, find and understand performance bottlenecks. But sometimes we just want to lay back, relax and still get a gist of the hot zones in our code. A picture is worth a thousand words.

profiling heatmap matplotlibpynamical uses pandas, numpy, and numba for fast simulation, and matplotlib for visualizations and animations to explore system behavior. Compatible with Python 2 and 3. Pynamical comes packaged with the logistic map, the Singer map, and the cubic map predefined. The models may be run with a range of parameter values over a set of time steps, and the resulting numerical output is returned as a pandas DataFrame. Pynamical can then visualize this output in various ways, including with bifurcation diagrams, two-dimensional phase diagrams, three-dimensional phase diagrams, and cobweb plots.

chaos nonlinear fractal logistic visualization modeling animation math physics pandas numba numpy matplotlib ipynb bifurcation-diagram fractals systems phase-diagram cobweb-plotA wind rose is a graphic tool used by meteorologists to give a succinct view of how wind speed and direction are typically distributed at a particular location. It can also be used to describe air quality pollution sources. The wind rose tool uses Matplotlib as a backend. Data can be passed to the package using Numpy arrays or a Pandas DataFrame. Windrose is a Python library to manage wind data, draw windroses (also known as polar rose plots), and fit Weibull probability density functions.

numpy pandas speed wind matplotlib windrose
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