Network-Intrusion-Detection-Using-Machine-Learning VS Food-Recipe-CNN

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

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Network-Intrusion-Detection-Using-Machine-Learning Food-Recipe-CNN
1 1
97 560
- -
1.8 0.0
over 2 years ago over 1 year ago
Jupyter Notebook Jupyter Notebook
GNU General Public License v3.0 only -
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.
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.

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.

Food-Recipe-CNN

Posts with mentions or reviews of Food-Recipe-CNN. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-08-16.

What are some alternatives?

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

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

Playing-Cards-Classification-TensorFlow-CNN - CNN Model to Classify Playing Cards

AlphaPy - Python AutoML for Trading Systems and Sports Betting

simplebendingpractice - BeamBending: a teaching aid for 1-D shear-force and bending-moment diagrams

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

CNN-Filter-DB - A database of over 1.4 billion 3x3 convolution filters extracted from hundreds of diverse CNN models with relevant meta information (CVPR 2022 ORAL)

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.

neuralnet-browser - Artificial Neural Network from scratch using Javascript on the browser

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

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

FLAML - A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.