Intro to TensorFlow 日本語版 from Coursera

What's inside

Syllabus

コースの概要

これは TensorFlow 2.x の入門コースです。TensorFlow 2.x では手軽な Keras を活用して機械学習モデルを作成できます。このコースでは、TensorFlow 2.x 入力データパイプラインの設計と作成、TensorFlow 2.x と Keras を使用した機械学習モデルの作成、機械学習モデルの精度向上、大規模に使用する機械学習モデルの記述について取り上げます。

TensorFlow の概要

TensorFlow 2.x の新しいパラダイムについて学びます。TensorFlow API の階層について学び、TensorFlow の主要コンポーネント、テンソル、および変数を実践演習で理解します。

TensorFlow 入力データパイプラインの設計と作成

データセットと特徴列の扱い方について学びます。tf.data.Dataset を使用して csv データ、NumPy 配列、テキストデータ、および画像を読み込む実践演習を行います。数値、カテゴリ、バケット、およびハッシュの特徴列を作成する実践演習も行います。

Tensorflow 2 と Keras Sequential API を使用したニューラルネットワークのトレーニング

このモジュールでは、Keras Sequential API を使用して TensorFlow モデルを記述することを学びます。ただし、モデルの記述の前に、活性化関数、損失、および最適化について学びます。次に、Keras Sequential API を使用してディープラーニングモデルを作成する方法を学びます。クラウドに予測モデルをデプロイする方法についても学びます。

Tensorflow 2 と Keras Functional API を使用したニューラルネットワークのトレーニング

Sequential モデル API はほとんどのディープラーニングモデルの開発に適していますが、制約がいくつかあります。その一例を挙げると、入力ソースが複数あるモデル、出力先が複数になるモデル、レイヤを再利用するモデルを定義するのは単純ではありません。Keras Functional API は tf.keras.Sequential API より柔軟にモデルを作成する手段です。Functional API は非線形トポロジのモデル、レイヤを共有するモデル、入力または出力が複数あるモデルに対応できます。Keras Functional API ではモデルを柔軟に定義できます。特に、入力または出力が複数あるモデルや、レイヤを共有するモデルを定義できます。アドホックの非巡回ネットワークグラフを定義することもできます。大抵のディープラーニングモデルの主な目的は、レイヤの有向非巡回グラフ（DAG）です。Functional API はレイヤのグラフを作成する手段です。モデルのパフォーマンス向上に役立つ正則化についても学びます。

まとめ

このコースでこれまでに取り上げた TensorFlow のトピックをここでまとめます。コア TensorFlow コード、tf.data API、Keras Sequential API、および Keras Functional API について復習し、最後には Cloud AI Platform での機械学習モデルのスケーリングについて取り上げます。

Good to know

Know what's good

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, and possible dealbreakers

Explores TensorFlow 2.x and Keras, which are standard tools in machine learning

Taught by Google Cloud Training, who are recognized for their work in the topic this course teaches

Develops TensorFlow input data pipelines and neural networks, which are core skills for machine learning professionals

Covers essential concepts of machine learning, such as activation functions, loss functions, and optimization algorithms

Provides hands-on labs and interactive materials to enhance learning

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Intro to TensorFlow 日本語版 with these activities:

復習: 線形代数

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TensorFlow 2.x と Keras を使用した機械学習モデルの作成には、線形代数の知識が不可欠です。このアクティビティにより、線形代数の基本事項を復習し、機械学習の基礎を固めることができます。

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行列演算の復習
ベクトルの内積と外積の計算練習
行列式の計算方法の確認

TensorFlow 2.x の公式チュートリアル

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TensorFlow 2.x の公式チュートリアルは、機械学習モデルを構築するための包括的なガイドです。このアクティビティにより、TensorFlow 2.x の基本を学び、機械学習のプロジェクトに活用することができます。

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「Hello World!」チュートリアルを完了する
線形回帰チュートリアルを完了する
CNN チュートリアルを完了する

TensorFlow コード演習

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コードを実際に書いて練習することで、TensorFlow 2.x の概念をより深く理解することができます。

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TensorFlow コード演習を見つける
演習を完了する
コードを理解し、独自のコードを書く

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学習グループへの参加

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学習グループに参加することで、他の学生とつながり、機械学習の概念について議論し、相互にサポートし合うことができます。

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学習グループを探す
学習グループのメンバーと定期的に会う
機械学習の概念について議論し、質問をする

TensorFlow 2.x ワークショップへの参加

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TensorFlow 2.x ワークショップは、TensorFlow 2.x の機能と機械学習の応用について学ぶのに役立つ、対面型のイベントです。このアクティビティを通じて、専門家から学び、他の参加者とネットワークを構築することができます。

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TensorFlow 2.x ワークショップを探す
ワークショップに参加する
TensorFlow 2.x の機能と応用について学ぶ

コース資料のまとめ

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コース資料をまとめておくと、学習した概念を復習し、コース終了後も参照できます。

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レクチャーノートをまとめる
課題と演習をまとめる
オンラインリソースとドキュメントをまとめる

Career center

Learners who complete Intro to TensorFlow 日本語版 will develop knowledge and skills that may be useful to these careers:

Computer Vision Engineer

For those aspiring to become a Computer Vision Engineer, the course **Intro to TensorFlow 日本語版** offered by Google Cloud is a valuable resource. The course provides a comprehensive overview of TensorFlow 2.x, a leading machine learning library, and teaches students how to use it to develop computer vision applications. Computer Vision Engineers use machine learning to analyze images and videos, and this course will give you the skills you need to succeed in this role.

See salaries and explore the career path for Computer Vision Engineer

Machine Learning Engineer

Those seeking to become a Machine Learning Engineer can take the course **Intro to TensorFlow 日本語版** offered by Google Cloud. The course will teach you how to design, implement, and evaluate machine learning models using TensorFlow 2.x and Keras. These skills are essential for Machine Learning Engineers, who are responsible for developing and deploying machine learning solutions. The course also provides hands-on experience with real-world datasets, making it ideal for those looking to gain practical experience in machine learning.

See salaries and explore the career path for Machine Learning Engineer

Artificial Intelligence Engineer

To become an Artificial Intelligence Engineer, taking the course **Intro to TensorFlow 日本語版** offered by Google Cloud is a wise choice. The course will teach you the fundamentals of TensorFlow 2.x, a popular machine learning library, and how to use it to design and implement AI solutions. As an Artificial Intelligence Engineer, you will be responsible for developing and deploying AI systems, and this course will provide you with the skills you need to succeed in this role.

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Natural Language Processing Engineer

To pursue a career as a Natural Language Processing Engineer, taking the course **Intro to TensorFlow 日本語版** offered by Google Cloud is a great starting point. The course will teach you the basics of TensorFlow 2.x, a popular machine learning library, and how to use it to develop natural language processing applications. As a Natural Language Processing Engineer, you will be responsible for developing and deploying NLP systems, and this course will give you the skills you need to succeed in this role.

See salaries and explore the career path for Natural Language Processing Engineer

Research Scientist

For those interested in a career as a Research Scientist, the course **Intro to TensorFlow 日本語版** offered by Google Cloud can provide valuable knowledge. The course provides a comprehensive overview of TensorFlow 2.x, a leading machine learning library, and teaches students how to use it to conduct research and develop new machine learning algorithms. Research Scientists use machine learning to solve complex problems, and this course will give you the skills you need to succeed in this role.

See salaries and explore the career path for Research Scientist

Machine Learning Researcher

The course **Intro to TensorFlow 日本語版** offered by Google Cloud can be beneficial for aspiring Machine Learning Researchers. The course provides a foundation in machine learning, a key skill for Machine Learning Researchers, and teaches students how to use TensorFlow 2.x to conduct research and develop new machine learning algorithms. Machine Learning Researchers use machine learning to solve complex problems, and this course will give you the skills you need to succeed in this role.

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Data Analyst

For those aspiring to become a Data Analyst, the course **Intro to TensorFlow 日本語版** offered by Google Cloud is a valuable resource. The course provides a comprehensive overview of TensorFlow 2.x, a leading machine learning library, and teaches students how to use it to analyze and interpret data. Data Analysts use machine learning techniques to extract insights from data, and this course will provide you with the skills you need to succeed in this role.

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Software Engineer

For individuals interested in a career as a Software Engineer, the course **Intro to TensorFlow 日本語版** offered by Google Cloud can provide a solid foundation. The course covers the fundamentals of TensorFlow 2.x, a popular open-source machine learning library, and teaches students how to design and implement machine learning models. This knowledge is highly sought after in the tech industry, and Software Engineers with expertise in machine learning are in high demand.

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Data Scientist

To become a Data Scientist, one could take the course **Intro to TensorFlow 日本語版** offered by Google Cloud. This course will help one develop skills to design and create TensorFlow models. As a Data Scientist, one will be able to use these models to analyze large datasets and extract meaningful insights. This course will also help one build a foundation in machine learning, which is a key skill for Data Scientists.

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Quantitative Analyst

For those interested in a career as a Quantitative Analyst, the course **Intro to TensorFlow 日本語版** offered by Google Cloud can be beneficial. The course provides a foundation in machine learning, a key skill for Quantitative Analysts, and teaches students how to use TensorFlow 2.x to analyze and interpret data. Quantitative Analysts use machine learning to make investment decisions, and this course will give you the skills you need to succeed in this role.

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Data Engineer

Those interested in becoming a Data Engineer can benefit from the course **Intro to TensorFlow 日本語版** offered by Google Cloud. The course provides an introduction to TensorFlow 2.x, a machine learning library, and teaches students how to use it to analyze and interpret data. Data Engineers use machine learning to build and maintain data pipelines, and this course will give you the skills you need to succeed in this role.

See salaries and explore the career path for Data Engineer

Market Researcher

For Market Researchers, the course **Intro to TensorFlow 日本語版** offered by Google Cloud can provide valuable knowledge. The course introduces TensorFlow 2.x, a machine learning library, and teaches students how to use it to analyze data and extract insights. Market Researchers use data to understand consumer behavior, and this course will equip you with the skills to succeed in this role.

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Business Analyst

Business Analysts can benefit from taking the course **Intro to TensorFlow 日本語版** offered by Google Cloud. The course teaches the basics of TensorFlow 2.x, a popular machine learning library, and how to use it to analyze data and solve business problems. Business Analysts use data to make informed decisions, and this course will give you the skills you need to succeed in this role.

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Statistician

The course **Intro to TensorFlow 日本語版** offered by Google Cloud could be helpful for aspiring Statisticians. The course provides an introduction to TensorFlow 2.x, a popular machine learning library, and teaches students how to use it to analyze and interpret data. Statisticians use machine learning to extract insights from data, and this course will provide you with the skills you need to succeed in this role.

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Intro to TensorFlow 日本語版

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