Network-Intrusion-Detection-Using-Machine-Learning
ydata-profiling
| Network-Intrusion-Detection-Using-Machine-Learning | ydata-profiling | |
|---|---|---|
| 1 | 43 | |
| 97 | 12,053 | |
| - | 0.9% | |
| 1.8 | 8.5 | |
| over 2 years ago | 9 days ago | |
| Jupyter Notebook | Python | |
| GNU General Public License v3.0 only | MIT License |
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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.
Network-Intrusion-Detection-Using-Machine-Learning
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Machine learning based network intrusion detection system
Theres quite a lot of work on this. One example of this is: https://github.com/abhinav-bhardwaj/Network-Intrusion-Detection-Using-Machine-Learning
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?
imodels - Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).
dtale - Visualizer for pandas data structures
AlphaPy - Python AutoML for Trading Systems and Sports Betting
DataProfiler - What's in your data? Extract schema, statistics and entities from datasets
data-science-ipython-notebooks - Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
dataframe-go - DataFrames for Go: For statistics, machine-learning, and data manipulation/exploration
One-Piece-Image-Classifier - A quick image classifier trained with manually selected One Piece images.
lux - Automatically visualize your pandas dataframe via a single print! 📊 💡
TensorFlow2.0_Notebooks - Implementation of a series of Neural Network architectures in TensorFow 2.0
get-started-with-JAX - The purpose of this repo is to make it easy to get started with JAX, Flax, and Haiku. It contains my "Machine Learning with JAX" series of tutorials (YouTube videos and Jupyter Notebooks) as well as the content I found useful while learning about the JAX ecosystem.
Food-Recipe-CNN - food image to recipe with deep convolutional neural networks.
evidently - Evaluate and monitor ML models from validation to production. Join our Discord: https://discord.com/invite/xZjKRaNp8b