June 2022
Intermediate to advanced
384 pages
6h 26m
Japanese
Content preview from 動かして学ぶAI・機械学習の基礎 ―TensorFlowによるコンピュータビジョン、自然言語処理、時系列データの予測とデプロイBecome an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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15章TensorFlow.jsの紹介
モバイル機器や組み込み機器での実行を可能にするTensorFlow Liteに加えて、TensorFlowエコシステムはTensorFlow.jsも提供します。これにより、一般的なJavaScript言語を使用して機械学習モデルを開発し、ブラウザでの直接実行や、Node.jsによるバックエンドでの使用が可能となります。TensorFlow.jsを使用すると、新しいモデルの学習やモデルを使用した推論が行えることに加えて、PythonベースのモデルをJavaScript互換のモデルに変換するツールも提供されています。本章では、エコシステムにおけるTensorFlow.jsの位置づけと、そのアーキテクチャを紹介します。また、ブラウザに統合された無料のオープンソースIDEを使用して、独自のモデルを構築する方法を学びます。
15.1 TensorFlow.jsとは
TensorFlowのエコシステムをまとめると、図15-1になります。モデルの学習を行うためのツール群、既存のモデルや層を保管するリポジトリ、そしてエンドユーザがモデルをデプロイするための一連の技術で構成されています。
（「12章 TensorFlow Liteの紹介」～「14章 iOSアプリでTensorFlow Lite」で紹介した）TensorFlow Liteや（「19章 TensorFlow Servingへのデプロイ」で取り上げる）TensorFlow Servingと同様に、TensorFlow.jsはこの図の右側に配置されています。これは、TensorFlow.jsが主にモデルのランタイムとして意図されている一方で、モデルの学習にも使用できることからPythonやSwiftと並んで第一級の言語であると考えるべきだからです。TensorFlow.jsはブラウザでもNode.jsのようなバックエンドでも実行できますが、本書では主にブラウザに焦点を当てます。 ...
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