automl VS TFLiteClassification

Compare automl vs TFLiteClassification and see what are their differences.

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automl TFLiteClassification
5 1
5,143 0
1.0% -
6.2 0.0
10 days ago over 1 year ago
Jupyter Notebook Jupyter Notebook
Apache License 2.0 -
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.

automl

Posts with mentions or reviews of automl. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-01-13.

TFLiteClassification

Posts with mentions or reviews of TFLiteClassification. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-03-08.

What are some alternatives?

When comparing automl and TFLiteClassification you can also consider the following projects:

poolformer - PoolFormer: MetaFormer Is Actually What You Need for Vision (CVPR 2022 Oral)

simple-faster-rcnn-pytorch - A simplified implemention of Faster R-CNN that replicate performance from origin paper

PAWS-TF - Minimal implementation of PAWS (https://arxiv.org/abs/2104.13963) in TensorFlow.

mmclassification - OpenMMLab Image Classification Toolbox and Benchmark

rpi-urban-mobility-tracker - The easiest way to count pedestrians, cyclists, and vehicles on edge computing devices or live video feeds.

SipMask - SipMask: Spatial Information Preservation for Fast Image and Video Instance Segmentation (ECCV2020)

node-efficientnet - tensorflowJS implementation of EfficientNet 🚀

BERT-for-Mobile - Compares the DistilBERT and MobileBERT architectures for mobile deployments.

mlkit - A collection of sample apps to demonstrate how to use Google's ML Kit APIs on Android and iOS

tflitego - tflitego provide a simple and clear solution to use TensorFlow lite in Go. Our objective is provide a cohesive API, simplicity related to TensorFlow Lite C API connection and maintainability.

kivy-tensorflow-helloworld - Run inference with Tensorflow Lite on iOS, Android, MacOS, Windows and Linux using Python

H2O - H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.