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  4. Website Accelerator
  5. TensorFlow vs Torbit vs xlwings

TensorFlow vs Torbit vs xlwings

OverviewDecisionsComparisonAlternatives

Overview

Torbit
Torbit
Stacks5
Followers15
Votes0
xlwings
xlwings
Stacks36
Followers125
Votes0
GitHub Stars0
Forks2
TensorFlow
TensorFlow
Stacks3.9K
Followers3.5K
Votes106
GitHub Stars192.3K
Forks74.9K

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Advice on Torbit, xlwings, TensorFlow

Adithya
Adithya

Student at PES UNIVERSITY

May 11, 2020

Needs advice

I have just started learning some basic machine learning concepts. So which of the following frameworks is better to use: Keras / TensorFlow/PyTorch. I have prior knowledge in python(and even pandas), java, js and C. It would be nice if something could point out the advantages of one over the other especially in terms of resources, documentation and flexibility. Also, could someone tell me where to find the right resources or tutorials for the above frameworks? Thanks in advance, hope you are doing well!!

107k views107k
Comments

Detailed Comparison

Torbit
Torbit
xlwings
xlwings
TensorFlow
TensorFlow

Torbit is a cloud-based website accelerator service that makes websites faster. Torbit speeds up your site by automating these performance optimizations that are otherwise tedious for you to do by hand.

Replace your VBA code with Python, a powerful yet easy-to-use programming language that is highly suited for numerical analysis. Supports Windows & Mac!

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.

The metrics you care about- With performance data, itʼs important to look beyond averages since outliers are inevitable. Insight allows you to look at other key metrics such as your median and key percentiles (90th, 95th & 99th).;Real visitor data- See a histogram showing the breakdown of your site speed and get a better sense of the typical experience for your visitors. With 100% sampling, youʼll get valuable performance data for every visitor on every page.;Real time feedback- Did that latest code deployment make your website faster or slower? Is your server having capacity issues? By tracking your performance in real time, you can see how your speed changes and what your visitors are experiencing right now. With 1-second resolution, you have instant transparency into how your site is performing at any given moment.;Spot performance issues right away- With our live map view, see the loading times your visitors are experiencing right now and spot any performance issues that may be affecting a particular region.
Easy deployment: The receiver of an xlwings-powered spreadsheets only needs Python with minimal dependencies — or nothing at all when shipped with the Python runtime.;Cross-Platform: xlwings works with Microsoft Excel on Windows and Mac.;Plug-and-Play: No cumbersome installation of Excel add-ins or license keys.;Flexible: Works with pretty much every combination of Excel and Python.;Two way communication: Call Python from Excel or interact with Excel from Python.;Free and open-source: xlwings is released under a permissive BSD-License.
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Statistics
GitHub Stars
-
GitHub Stars
0
GitHub Stars
192.3K
GitHub Forks
-
GitHub Forks
2
GitHub Forks
74.9K
Stacks
5
Stacks
36
Stacks
3.9K
Followers
15
Followers
125
Followers
3.5K
Votes
0
Votes
0
Votes
106
Pros & Cons
No community feedback yet
Cons
  • 3
    Very slow and still needs VBA for UDFs
Pros
  • 32
    High Performance
  • 19
    Connect Research and Production
  • 16
    Deep Flexibility
  • 12
    Auto-Differentiation
  • 11
    True Portability
Cons
  • 9
    Hard
  • 6
    Hard to debug
  • 2
    Documentation not very helpful
Integrations
No integrations availableNo integrations available
JavaScript
JavaScript

What are some alternatives to Torbit, xlwings, TensorFlow?

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.

Airtable

Airtable

Working with Airtable is as fast and easy as editing a spreadsheet. But only Airtable is backed by the power of a full database, giving you rich features far beyond what a spreadsheet can offer.

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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