Network-Intrusion-Detection-Using-Machine-Learning VS Workshops

Compare Network-Intrusion-Detection-Using-Machine-Learning vs Workshops and see what are their differences.

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Network-Intrusion-Detection-Using-Machine-Learning Workshops
1 1
97 355
- 0.3%
1.8 6.3
over 2 years ago 5 months ago
Jupyter Notebook Jupyter Notebook
GNU General Public License v3.0 only MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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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

Posts with mentions or reviews of Network-Intrusion-Detection-Using-Machine-Learning. We have used some of these posts to build our list of alternatives and similar projects.

Workshops

Posts with mentions or reviews of Workshops. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing Network-Intrusion-Detection-Using-Machine-Learning and Workshops you can also consider the following projects:

imodels - Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).

tensor-house - A collection of reference Jupyter notebooks and demo AI/ML applications for enterprise use cases: marketing, pricing, supply chain, smart manufacturing, and more.

AlphaPy - Python AutoML for Trading Systems and Sports Betting

it-salary-analysis - 💰 Analysis of Salaries in IT Roles: DevOps, Cyber Security, and AI

ydata-profiling - 1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.

artificial-self-AMLD-2020 - Workshop material for the AMLD 2020 workshop on "Meet your Artificial Self: Generate text that sounds like you"

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.

nlpaug - Data augmentation for NLP

One-Piece-Image-Classifier - A quick image classifier trained with manually selected One Piece images.

ZeroSync - A STARK proof to sync a Bitcoin full node in an instant.

TensorFlow2.0_Notebooks - Implementation of a series of Neural Network architectures in TensorFow 2.0

100DaysOfML - 100 Days Of Machine Learning. New Content in every 1-2 day and projects every week. The massive 100DaysOfML in building