cheatsheets
examples
Our great sponsors
cheatsheets | examples | |
---|---|---|
126 | 142 | |
7,219 | 7,699 | |
0.9% | 1.2% | |
7.1 | 6.2 | |
24 days ago | 7 days ago | |
Python | Jupyter Notebook | |
BSD 2-clause "Simplified" License | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
cheatsheets
-
Mastering Matplotlib: A Step-by-Step Tutorial for Beginners
Matplotlib - A Python 2D plotting library.
- Ask HN: What plotting tools should I invest in learning?
- Help with an array
-
PSA: You don't need fancy stuff to do good work.
Python's pandas, NumPy, and SciPy libraries offer powerful functionality for data manipulation, while matplotlib, seaborn, and plotly provide versatile tools for creating visualizations. Similarly, in R, you can use dplyr, tidyverse, and data.table for data manipulation, and ggplot2, lattice, and shiny for visualization. These packages enable you to create insightful visualizations and perform statistical analyses without relying on expensive or proprietary software.
-
What else should I complete before applying for a data analyst role?
programming language: basic python, pandas, matplotlib -- you'll probably do these in school, but if not https://cs50.harvard.edu/python/2022/ https://matplotlib.org/
-
[OC] Analyzing 15,963 Job Listings to Uncover the Top Skills for Data Analysts (update)
Analysis was done in Jupyter Notebook with Python 3.10, Pandas, Matplotlib, wordcloud and Mercury framework.
-
[OC] Data Analyst Skills in need based on 15,963 job listings
Analysis was done in Jupyter Notebook with Python 3.10 kernel, Pandas, Matplotlib, wordcloud and Mercury framework to share notebook as a web application with widgets and code hidden. Gif created in Canva.
-
About to lose access to MATLAB, is Python a realistic replacement for DSP algorithm development?
Edit: recommended libraries A python version of Matlab plotting down to the syntaxes matching.
- What is something you wish there was a Python module for?
-
Suggestions for Udemy, Coursera, DataCamp, Pluralsight courses for Pandas and Visualization? So many options out there...project-based ones would be ideal. Or the ones to avoid or overrated courses?
https://matplotlib.org https://seaborn.pydata.org
examples
-
Open Source Ascendant: The Transformation of Software Development in 2024
AI's Open Embrace Artificial intelligence (AI) and machine learning (ML) are increasingly leveraging open-source frameworks like TensorFlow [https://www.tensorflow.org/] and PyTorch [https://pytorch.org/]. This democratization of AI tools is driving innovation and lowering entry barriers across industries.
-
Best AI Tools for Students Learning Development and Engineering
Which label applies to a tool sometimes depends on what you do with it. For example, PyTorch or TensorFlow can be called a library, a toolkit, or a machine-learning framework.
-
Releasing The Force Of Machine Learning: A Noviceโs Guide ๐
TensorFlow: An open-source machine learning framework for high-performance numerical computations, especially well-suited for deep learning.
-
MLOps in practice: building and deploying a machine learning app
The tool used to build the model per se was TensorFlow, a very powerful and end-to-end open source platform for machine learning with a rich ecosystem of tools. And in order to to create the needed script using TensorFlow Jupyter Notebook was used, which is a web-based interactive computing platform.
-
๐ฅ14 Excellent Open-source Projects for Developers๐
10. TensorFlow - Make Machine Learning Work for You ๐ค
-
๐ฅ๐ Top 10 Open-Source Must-Have Tools for Crafting Your Own Chatbot ๐ค๐ฌ
#2 TensorFlow
- Are there people out there who still like Sam atlman - AI IS AT DANGER
-
How popular are libraries in each technology
Machine learning is the process of using algorithms and statistical models to enable computers to learn from data. There are many tools and libraries available for machine learning, but the most popular by far is TensorFlow. TensorFlow is an open-source platform for machine learning developed by Google. It has over 176k stars on Github and is used by companies such as Airbnb and Intel.
-
React + Tensorflow.js , a cool recipe for AI powered applications
Tensorflow is Google's "end-to-end machine learning platform". It's a framework to manage the whole lifecycle of a Machine Learning (and AI) project, from data preparation to production deployment. Remember the math stuff we talked about in the last section? Tensorflow manages that in addition to a lot of other stuff. Its core API is written for Python and you have to know your math just a little bit in order to play with it. It's more for deep learning models (neural networks) and has a lot of already implemented "layers" for you to use in your network. You can prepare data (images included with the option of image augmentation for small data sets ... yay! ๐), experiment with different model architectures, tune the model's hyperparameters (a fancy name for model configs), train, validate and test your models and monitor your models in production. It's a great framework, but it is not an easy one to learn, especially if you don't like math that much!
-
List of AI-Models
Click to Learn more...
What are some alternatives?
finplot - Performant and effortless finance plotting for Python
cppflow - Run TensorFlow models in C++ without installation and without Bazel
manim - A community-maintained Python framework for creating mathematical animations.
Fast-F1 - FastF1 is a python package for accessing and analyzing Formula 1 results, schedules, timing data and telemetry
mlpack - mlpack: a fast, header-only C++ machine learning library
awesome-teachable-machine - Useful resources for creating projects with Teachable Machine models + curated list of already built Awesome Apps!
face-api.js - JavaScript API for face detection and face recognition in the browser and nodejs with tensorflow.js
Selenium WebDriver - A browser automation framework and ecosystem.
Apache Spark - Apache Spark - A unified analytics engine for large-scale data processing
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
aws-graviton-getting-started - Helping developers to use AWS Graviton2 and Graviton3 processors which power the 6th and 7th generation of Amazon EC2 instances (C6g[d], M6g[d], R6g[d], T4g, X2gd, C6gn, I4g, Im4gn, Is4gen, G5g, C7g[d][n], M7g[d], R7g[d]).
Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more