Skip to main content

Introduction

The SAP Federated ML Python libraries (FedML) applies the Data Federation architecture of SAP Datasphere for intelligently sourcing SAP as well as non-SAP data for Machine Learning experiments done at any Machine Learning platform thereby removing the need for replicating or moving data. By abstracting the Data Connection and Data load , the FedML library provides end to end platform agnostic integration support for instant data access & discovery of semantically rich business data with just few lines of code.

Installation

Install the SAP FedML library using pip as follows:

pip install fedml-dsp

Documentation and getting started

For getting started with the SAP FedML Library and for documentation and sample notebooks, please refer the SAP FedML documentation here.

Metadata

Release files for fedml-dsp 1.0.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for fedml-dsp 1.0.0
File Size Uploaded
fedml_dsp-1.0.0.tar.gz 8.2 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for fedml-dsp 1.0.0
File Interpreter ABI Platform
fedml_dsp-1.0.0-py3-none-any.whl Python 3 none any Details

Total release size: 16.1 kB

Release files / fedml_dsp-1.0.0.tar.gz

Download URL fedml_dsp-1.0.0.tar.gz
Size 8.2 kB
Tags Source
SHA-256 checksum
How to use checksums
2d89a19647c7973ecf4c3138420b53befd27fb9142db933ae9742fd917a0267e
BLAKE2b-256 checksum
How to use checksums
b9330f887fbae37f51e34f3ba17102fd03dd0ef6c21b9633108af81eed836499
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/5.0.0 CPython/3.9.9

Release files / fedml_dsp-1.0.0-py3-none-any.whl

Download URL fedml_dsp-1.0.0-py3-none-any.whl
Size 7.9 kB
Tags Python 3
SHA-256 checksum
How to use checksums
b17ee773abd14ba98b1bce739d0bbbdcabfd836ac81429e59651a384c015084b
BLAKE2b-256 checksum
How to use checksums
0848027a73b67e28ebb5fee3639dd2e71e9e43a6aecbebe1a59d85458a3d8d54
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/5.0.0 CPython/3.9.9

Release history Release notifications | RSS feed

This release

1.0.0 This release

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page