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ML development requires using a variety of constantly
evolving tools and frameworks. New ML tools continue to emerge as ways to handle
complex data types, advances in hardware, and techniques for orchestrating
pipelines continue to develop.
As a result, companies, organizations, and teams implement
ML solutions using different tools and frameworks, which likely
change over time.
While common frameworks and best practices are emerging, keep in mind that the
nature of your particular problem might require custom solutions in certain
cases. The following sections provide links to resources for getting started
with ML and AI development.
Tools and frameworks for building ML and AI applications and products:
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-02-26 UTC."],[[["Machine learning (ML) development involves the use of various evolving tools and frameworks, leading to diverse implementation approaches across different entities."],["While common practices are emerging in ML, custom solutions may be necessary depending on the specific problem."],["Google provides resources for ML development, including tools and frameworks, as well as a community for sharing models and datasets."],["Further learning opportunities are available through Google's machine learning courses."]]],[]]