Search Results for "matplotlib-1.5.2"
Sort By:
Showing 9 open source projects for "matplotlib-1.5.2"
View related business solutions-
Go from Data Warehouse to Data and AI platform with BigQueryBigQuery is more than a data warehouse—it's an autonomous data-to-AI platform. Use familiar SQL to train ML models, run time-series forecasts, and generate AI-powered insights with native Gemini integration. Built-in agents handle data engineering and data science workflows automatically. Get $300 in free credit, query 1 TB, and store 10 GB free monthly.
-
$300 in Free Credit for Your Google Cloud ProjectsLaunch your next project with $300 in free Google Cloud credit—no hidden charges. Test, build, and deploy without risk. Use your credit across the Google Cloud platform to find what works best for your needs. After your credits are used, continue building with free monthly usage products. Only pay when you're ready to scale. Sign up in minutes and start exploring.
-
1
Matplotlib
matplotlib: plotting with Python
Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python. Matplotlib makes easy things easy and hard things possible. Matplotlib ships with several add-on toolkits, including 3D plotting with mplot3d, axes helpers in axes_grid1 and axis helpers in axisartist. A large number of third party packages extend and build on Matplotlib functionality, including several higher-level plotting interfaces (seaborn, HoloViews, ggplot, ...), and a projection and mapping toolkit (Cartopy). ... -
2
Peroxide
Rust numeric library with high performance and friendly syntax
Rust numeric library contains linear algebra, numerical analysis, statistics and machine learning tools with R, MATLAB, Python-like macros. Peroxide uses a 1D data structure to represent matrices, making it straightforward to integrate with BLAS (Basic Linear Algebra Subprograms). This means that Peroxide can guarantee excellent performance for linear algebraic computations by leveraging the optimized routines provided by BLAS. For users familiar with numerical computing libraries like... -
3
Homemade Machine Learning
Python examples of popular machine learning algorithms
...The purpose is pedagogical: you’ll see linear regression, logistic regression, k-means clustering, neural nets, decision trees, etc., built in Python using fundamentals like NumPy and Matplotlib, not hidden behind API calls. It is well suited for learners who want to move beyond library usage to understand how algorithms operate internally—how cost functions, gradients, updates and predictions work. -
4
vim-jukit
Jupyter-Notebook inspired Neovim/Vim Plugin
REPL plugin and Jupyter-Notebook alternative for (Neo)Vim. This plugin is aimed at users in search for a REPL plugin with lots of additional features. -
Run Any Workload on Compute Engine VMsCompute Engine delivers high-performance virtual machines for web apps, databases, containers, and AI workloads. Choose from general-purpose, compute-optimized, or GPU/TPU-accelerated machine types—or build custom VMs to match your exact specs. With live migration and automatic failover, your workloads stay online. New customers get $300 in free credits.
-
5
Zipline
Zipline, a Pythonic algorithmic trading library
Zipline is a Pythonic algorithmic trading library. It is an event-driven system for backtesting. Zipline is currently used in production as the backtesting and live-trading engine powering Quantopian -- a free, community-centered, hosted platform for building and executing trading strategies. Quantopian also offers a fully managed service for professionals that includes Zipline, Alphalens, Pyfolio, FactSet data, and more. Installing Zipline is slightly more involved than the average Python... -
6
Brand new cheatsheets and handouts
Matplotlib 3.1 cheat sheet
...For practitioners working on data-heavy projects, dashboards, or research code where plotting is frequent, it helps speed up development by reducing context-switching and documentation navigation overhead. It is especially useful when you know roughly what you want (e.g. “I need a scatter + histogram marginal plot”) but don’t remember the exact Matplotlib call. -
7
The Neural Process Family
This repository contains notebook implementations
...Each notebook includes theoretical explanations, key building blocks, and executable code that runs directly in Google Colab, requiring no local setup. Implementations rely only on standard dependencies such as NumPy, TensorFlow, and Matplotlib, and provide visualizations of model performance. -
8
data-science-ipython-notebooks
Data science Python notebooks: Deep learning
Data Science IPython Notebooks is a broad, curated set of Jupyter notebooks covering Python, data wrangling, visualization, machine learning, deep learning, and big data tools. It aims to be a practical map of the ecosystem, showing hands-on examples with libraries such as NumPy, pandas, matplotlib, scikit-learn, and others. Many notebooks introduce concepts step by step, then apply them to real datasets so readers can see techniques in action. Advanced sections touch on neural networks and distributed computing topics, helping you bridge from basics to production-adjacent workflows. The collection is suitable for self-paced study, quick reference, or as teaching materials in workshops. ... -
9
Zebra_Form
A jQuery augmented PHP library for creating and validating HTML forms
...When generated automatically, the generated output validates as HTML 4.01 Strict/XHTML 1.0 Strict/HTML5 and has the same look & feel across all major browsers like Firefox, Chrome, Opera, Safari, Internet Explorer 6+. The client-side validation is based on jQuery 1.5.2+ -
AI-powered service management for IT and enterprise teamsGive your IT, operations, and business teams the ability to deliver exceptional services—without the complexity. Maximize operational efficiency with refreshingly simple, AI-powered Freshservice.
- Previous
- You're on page 1
- Next
