get-started-with-JAX
ydata-profiling
| get-started-with-JAX | ydata-profiling | |
|---|---|---|
| 3 | 43 | |
| 558 | 12,053 | |
| - | 0.9% | |
| 0.0 | 8.5 | |
| 5 months ago | 10 days ago | |
| Jupyter Notebook | Python | |
| MIT License | MIT License |
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.
get-started-with-JAX
- How to stay up-to-date with the latest AI company announcements and events?
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Tips to become self taught machine learning engineer
The AI Epiphany
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Machine Learning with JAX - From Hero to HeroPro+ | Tutorial #2
Code: https://github.com/gordicaleksa/get-started-with-JAX
ydata-profiling
- FLaNK 25 December 2023
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First 15 Open Source Advent projects
6. Ydata-synthetic and Ydata-profiling by YData | Github | tutorial
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Coding Wonderland: Contribute to YData Profiling and YData Synthetic in this Advent of Code
Send us your North ⭐️: "On the first day of Christmas, my true contributor gave to me..." a star in my GitHub tree! 🎵 If you love these projects too, star ydata-profiling or ydata-synthetic and let your friends know why you love it so much!
- Data exploration is not dead
- Explore your data in a single line of code
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Which preprocessing steps to improve the performance of a naive bayes classifier
My suggestion start with the EDA - there are a lot of packages that automate that for you already. My usual go-to: https://github.com/ydataai/ydata-profiling.
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Simulating sales data
If you're not sure about the behaviour of your data (i.e., if the original data has properties like seasonality), you can use ydata-profiling to profile your data first.
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I recorded a Data Science Project using Python and uploaded it on Youtube
Super cool! For EDA, you could give ydata-profiling a spin sometime and speed up the process!
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Ydata-Profiling and Dask
Hey guys,
We've been recently at the Dask Demo Day and we're hoping to launch a new feature on ydata-profiling, with the support for Dask dataframes!
We're looking for Dask Wizards to start collaborating on this feature, so if you're interested, please join us to define the roadmap of the project and start making it real
Current GitHub branch is here: https://github.com/ydataai/ydata-profiling/tree/feat/dask
Dedicated dask channel here: https://discord.gg/EHDBuSSDuy
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🧠 ydata-profiling + Dask!
We're looking for Dask Wizards 🧙🏻♂️ to start collaborating on this branch, so if you're interested, please join us to define the roadmap of the project and start making it real 🚀
What are some alternatives?
Real-time-Object-Detection-for-Autonomous-Driving-using-Deep-Learning - My Computer Vision project from my Computer Vision Course (Fall 2020) at Goethe University Frankfurt, Germany. Performance comparison between state-of-the-art Object Detection algorithms YOLO and Faster R-CNN based on the Berkeley DeepDrive (BDD100K) Dataset.
dtale - Visualizer for pandas data structures
awesome-jax - JAX - A curated list of resources https://github.com/google/jax
DataProfiler - What's in your data? Extract schema, statistics and entities from datasets
Human-pose-estimation - A quick tutorial on multi-pose estimation with OpenCV, Tensorflow and MoveNet lightning.
dataframe-go - DataFrames for Go: For statistics, machine-learning, and data manipulation/exploration
JustEnoughScalaForSpark - A tutorial on the most important features and idioms of Scala that you need to use Spark's Scala APIs.
lux - Automatically visualize your pandas dataframe via a single print! 📊 💡
TF_JAX_tutorials - All about the fundamental blocks of TF and JAX!
evidently - Evaluate and monitor ML models from validation to production. Join our Discord: https://discord.com/invite/xZjKRaNp8b
tensor-sensor - The goal of this library is to generate more helpful exception messages for matrix algebra expressions for numpy, pytorch, jax, tensorflow, keras, fastai.
dataprep - Open-source low code data preparation library in python. Collect, clean and visualization your data in python with a few lines of code.