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  1. Stackups
  2. AI
  3. Development & Training Tools
  4. Machine Learning Tools
  5. PyBrain vs Tensorflow Lite

PyBrain vs Tensorflow Lite

OverviewComparisonAlternatives

Overview

Tensorflow Lite
Tensorflow Lite
Stacks74
Followers144
Votes1
PyBrain
PyBrain
Stacks0
Followers6
Votes0

PyBrain vs Tensorflow Lite: What are the differences?

What is PyBrain? A modular Machine Learning Library for Python. It's goal is to offer flexible, easy-to-use yet still powerful algorithms for Machine Learning Tasks and a variety of predefined environments to test and compare your algorithms.

What is Tensorflow Lite? Deploy machine learning models on mobile and IoT devices. It is a set of tools to help developers run TensorFlow models on mobile, embedded, and IoT devices. It enables on-device machine learning inference with low latency and a small binary size.

PyBrain and Tensorflow Lite can be primarily classified as "Machine Learning" tools.

Some of the features offered by PyBrain are:

  • Supervised Learning
  • Unsupervised Learning
  • Reinforcement Learning

On the other hand, Tensorflow Lite provides the following key features:

  • Lightweight solution for mobile and embedded devices
  • Enables low-latency inference of on-device machine learning models with a small binary size
  • Fast performance

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Detailed Comparison

Tensorflow Lite
Tensorflow Lite
PyBrain
PyBrain

It is a set of tools to help developers run TensorFlow models on mobile, embedded, and IoT devices. It enables on-device machine learning inference with low latency and a small binary size.

It's goal is to offer flexible, easy-to-use yet still powerful algorithms for Machine Learning Tasks and a variety of predefined environments to test and compare your algorithms.

Lightweight solution for mobile and embedded devices; Enables low-latency inference of on-device machine learning models with a small binary size; Fast performance
Supervised Learning; Unsupervised Learning; Reinforcement Learning; Black-box Optimization; Network Architectures; Toy Environments; 3D Environments; Function Environments; Pole-Balancing
Statistics
Stacks
74
Stacks
0
Followers
144
Followers
6
Votes
1
Votes
0
Pros & Cons
Pros
  • 1
    .tflite conversion
No community feedback yet
Integrations
Python
Python
Android OS
Android OS
iOS
iOS
Raspberry Pi
Raspberry Pi
Python
Python

What are some alternatives to Tensorflow Lite, PyBrain?

TensorFlow

TensorFlow

TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.

scikit-learn

scikit-learn

scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.

PyTorch

PyTorch

PyTorch is not a Python binding into a monolothic C++ framework. It is built to be deeply integrated into Python. You can use it naturally like you would use numpy / scipy / scikit-learn etc.

Keras

Keras

Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano. https://keras.io/

Kubeflow

Kubeflow

The Kubeflow project is dedicated to making Machine Learning on Kubernetes easy, portable and scalable by providing a straightforward way for spinning up best of breed OSS solutions.

TensorFlow.js

TensorFlow.js

Use flexible and intuitive APIs to build and train models from scratch using the low-level JavaScript linear algebra library or the high-level layers API

Polyaxon

Polyaxon

An enterprise-grade open source platform for building, training, and monitoring large scale deep learning applications.

Streamlit

Streamlit

It is the app framework specifically for Machine Learning and Data Science teams. You can rapidly build the tools you need. Build apps in a dozen lines of Python with a simple API.

MLflow

MLflow

MLflow is an open source platform for managing the end-to-end machine learning lifecycle.

H2O

H2O

H2O.ai is the maker behind H2O, the leading open source machine learning platform for smarter applications and data products. H2O operationalizes data science by developing and deploying algorithms and models for R, Python and the Sparkling Water API for Spark.

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