# tobegit3hub/tensorflow_template_application

TensorFlow template application for deep learning

Repository: https://github.com/tobegit3hub/tensorflow_template_application
Canonical: https://ross.abutalabs.com/products/tensorflow_template_application
Language: Python
License: Apache-2.0
License Family: permissive
Topics: tensorflow, tfrecords, libsvm, csv, deep-learning, machine-learning, mlp, cnn, lstm, inference, tensorboard, wide-and-deep, serving
Last push: 2023-07-05T20:27:20+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3698, "days_push": 1155, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1874, forks 702 (observed 2026-08-28T04:05:47.224271+00:00)

## What it is
A template application demonstrating end-to-end deep learning with TensorFlow, covering data formats (CSV, LIBSVM, TFRecords), multiple network models (DNN, CNN, LSTM, wide-and-deep), distributed training, and serving via TensorFlow Serving or HTTP. It includes gRPC predict clients in Python, Java, Scala, Go, C++, plus Android and iOS clients.

## Use cases
- learn tensorflow deep learning end to end
- template project for training tensorflow models
- serve a tensorflow model with grpc clients
- convert csv or libsvm data to tfrecords
- run distributed tensorflow training
- example wide and deep model implementation
- benchmark tensorflow training configurations

## When to choose
- learning TensorFlow 1.x workflows with a complete reference example
- bootstrapping a classic deep learning pipeline with training, export, and serving
- needing multi-language gRPC client examples for TensorFlow Serving

## When to avoid
- starting new projects on modern TensorFlow 2.x or PyTorch
- needing actively maintained production code
- looking for state-of-the-art model architectures

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: deep-learning, machine-learning, llm-training, sdk
- domain: deep-learning, machine-learning, developer-tools, tutorials
- platform: python, cross-platform
- tags: tensorflow, template-application, tfrecords, wide-and-deep, tensorboard, model-serving, distributed-training, grpc-client, sample-code

## Member repositories
- tobegit3hub/tensorflow_template_application (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:47.224271+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T03:14:48.735080+00:00, confidence not recorded.
  - readme: https://github.com/tobegit3hub/tensorflow_template_application (fetched 2026-08-28T04:05:47.224271+00:00, sha 56882ad41bb4)
- Data as of 2026-08-30T08:39:29.467469+00:00.