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AI、機械学習、ディープラーニングのための TensorFlow 入門

ソフトウェア開発者であれば、拡張性のあるAI搭載アルゴリズムを構築したい場合、構築ツールの使い方を理解する必要があります。この講座は今後学んでいく「TensorFlow in Practice 専門講座」の一部であり、機械学習用の人気のオープンソースフレームワークであるTensorFlowのベストプラクティスを学習します。

アンドリュー・エンの「 The Machine Learning（機械学習）」と「Deep Learning Specialization（ディープラーニング専門講座）」では、機械学習とディープラーニングの最も重要かつ基本的な原理を学習します。deeplearning.aiが提供する新しい「TensorFlow in Practice 専門講座」では、TensorFlowを使用してそれらの原理を実装し、拡張性のあるモデルを構築して現実世界の問題に適用する方法を学びます。ニューラルネットワークの仕組みについての理解を深めるには、「ディープラーニング専門講座」を受講することをお勧めします。

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Syllabus

新しいプログラミングパラダイム　

TensorFlowの入門～上級者向け講座へようこそ。お会いできて嬉しいです。１週目では、機械学習とディープラーニングの概要に触れ、それらがどのようにして新しいプログラミングパラダイムを提供し、これまで未踏だったシナリオを開くための新しいツールセットを提供するのかを簡単にご紹介します。必要なのは、基本的なプログラミングスキルだけで、あとは学習を進める中で習得できます。TensorFlow 1.ｘとTensorFlow 2.0アルファ版の両方で動作するコードを使って学んでいきます。まず、最初の動画で、アンドリューとローレンスの対話をご覧ください。これから学習するテーマについて話しています。

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Develops skills using industry standard programming tools for TensorFlow

Uses both TensorFlow 1.x and 2.x for added flexibility for learners at different stages

Addresses the growing need for real-world applications in the field of machine learning

Taught by industry experts Laurence Moroney and Andrew Ng

Not a standalone course, this is part of a multipart series

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Reviews summary

Tensorflow実践入門：ai・ml・dl応用

学習者によると、このコースはTensorFlowの実践的な基礎を習得するのに非常に効果的です。新しいプログラミングパラダイムとしてAI、機械学習、ディープラーニングの核となる概念をTensorFlowで実装する手法を学びます。特にハンズオン演習とコンピュータビジョンへの応用が評価される一方、一部の学習者には前提知識の確認が必要かもしれません。TensorFlowのバージョンに関する注意点も考慮すべき点として挙げられます。

分かりやすく構成されており、順序立てて学習を進められます。

"<positive>各週のテーマ</positive>が明確で、<positive>段階的に難易度が上がる</positive>ため、無理なく学習できました。"

"<positive>講師の説明</positive>が非常に分かりやすく、複雑な概念もスムーズに理解できました。"

"入門とありますが、<positive>機械学習の基礎</positive>からTensorFlowへの橋渡しが<positive>見事に構成</positive>されています。"

TensorFlowの実装を通じた具体的な応用力が身につきます。

"理論だけでなく、TensorFlowを使った<positive>具体的な実装方法</positive>を学べて、<positive>すぐに活用できる</positive>と感じました。"

"<positive>ハンズオン演習</positive>が多く、コードを書きながら理解を深められるので、非常に役立ちます。"

"<positive>現実世界の問題</positive>にTensorFlowを適用する<positive>実践的なスキル</positive>が身につきます。"

コースには複数のTensorFlowバージョンへの言及があります。

"TensorFlow 1.xと2.0アルファの両方で動くコードとありましたが、<negative>少し混乱する部分</negative>もありました。最新版に統一されているとより良いです。"

"コードが<negative>古いTensorFlowバージョン</negative>に基づいている部分があり、<negative>環境構築</negative>に手間取りました。"

"コースは素晴らしいですが、<warning>TensorFlowの急速な進化</warning>を考えると、内容の更新は定期的に必要だと感じます。"

基本的なプログラミングスキルやML/DLの理解が推奨されます。

"「入門」という名前ですが、<warning>ある程度のプログラミング経験</warning>がないと、少し難しく感じるかもしれません。"

"<warning>アンドリュー・エンの他の講座</warning>を先に受講していたので、<positive>スムーズに内容が理解</positive>できました。未受講だと大変かも。"

"<warning>基本的なPythonの知識</warning>は必須だと感じました。全くの初心者にはハードルが高いかもしれません。"

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 AI、機械学習、ディープラーニングのための TensorFlow 入門 with these activities:

Review Tensorflow basics

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Familiarizing yourself with Tensorflow basics will prepare you for the more advanced concepts covered in this course.

Browse courses on TensorFlow

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Revisit your notes or online resources on Tensorflow concepts.
Review code examples from the Tensorflow documentation.
Practice implementing simple Tensorflow models.

Complete guided tutorials on Computer Vision

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Following guided tutorials will provide you with practical experience in Computer Vision, a key topic in this course.

Browse courses on Computer Vision

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Identify online tutorials or workshops on Computer Vision fundamentals.
Follow the tutorials step-by-step, implementing the concepts in Tensorflow.
Experiment with different parameters and datasets to enhance your understanding.

Mentor peers on TensorFlow concepts

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Mentoring others will enhance your understanding of TensorFlow and reinforce your skills through teaching.

Browse courses on Mentoring

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Identify opportunities to assist classmates or colleagues who may need guidance with TensorFlow concepts.
Prepare and articulate explanations of TensorFlow topics clearly and effectively.
Provide constructive feedback and support to those you mentor.

Four other activities

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Solve practice problems on Convolutional Neural Networks

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Solving practice problems will reinforce your understanding of Convolutional Neural Networks, a crucial component in this course.

Browse courses on Convolutional Neural Networks

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Find online platforms or textbooks that offer practice problems on CNNs.
Attempt to solve the problems independently, implementing the solutions in Tensorflow.
Review your solutions against provided answers or consult online forums for guidance.

Start a project to build a deep learning model

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Initiating a project will provide you with hands-on experience in designing and implementing deep learning models.

Browse courses on Deep Learning Models

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Define the scope and objectives of your project.
Gather and prepare the necessary data for your model.
Choose an appropriate deep learning architecture and implement it using Tensorflow.
Train and evaluate your model, iterating to improve its performance.
Deploy your model and monitor its performance in a real-world setting.

Create a project using Tensorflow

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Developing a project will allow you to apply your knowledge of Tensorflow and demonstrate your skills in a practical setting.

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Identify a problem or challenge that you can solve using Tensorflow.
Design a solution and implement it using Tensorflow, considering performance and efficiency.
Document your project, including the problem statement, approach, and results.
Share your project on platforms like GitHub or Kaggle to receive feedback and connect with the community.

Participate in a Kaggle competition using Tensorflow

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Engaging in a Kaggle competition will challenge you to apply your Tensorflow skills in a competitive environment.

Browse courses on Kaggle Competitions

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Identify an appropriate Kaggle competition that aligns with your interests and skill level.
Study the competition guidelines and data provided.
Develop a solution using TensorFlow, optimizing for performance and accuracy.
Submit your solution and monitor your progress on the leaderboard.
Analyze the results and learn from the approaches of top-performing teams.

Career center

Learners who complete AI、機械学習、ディープラーニングのための TensorFlow 入門 will develop knowledge and skills that may be useful to these careers:

Artificial Intelligence Engineer

Artificial Intelligence Engineers design, develop, and deploy artificial intelligence systems. They work with a variety of programming languages and software development tools to create systems that can learn from data and make predictions. This course may be useful in helping you develop the skills and knowledge you need to succeed in this role.

See salaries and explore the career path for Artificial Intelligence Engineer

Deep Learning Engineer

Deep Learning Engineers design, develop, and deploy deep learning systems. They work with a variety of programming languages and software development tools to create systems that can learn from data and make predictions. This course may be useful in helping you develop the skills and knowledge you need to succeed in this role.

See salaries and explore the career path for Deep Learning Engineer

Computer Vision Engineer

Computer Vision Engineers design, develop, and deploy computer vision systems. They work with a variety of programming languages and software development tools to create systems that can see and understand the world around us. This course may be useful in helping you develop the skills and knowledge you need to succeed in this role.

See salaries and explore the career path for Computer Vision Engineer

Natural Language Processing Engineer

Natural Language Processing Engineers design, develop, and deploy natural language processing systems. They work with a variety of programming languages and software development tools to create systems that can understand and generate human language. This course may be useful in helping you develop the skills and knowledge you need to succeed in this role.

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

Speech Recognition Engineer

Speech Recognition Engineers design, develop, and deploy speech recognition systems. They work with a variety of programming languages and software development tools to create systems that can recognize and understand human speech. This course may be useful in helping you develop the skills and knowledge you need to succeed in this role.

See salaries and explore the career path for Speech Recognition Engineer

Machine Learning Researcher

Machine Learning Researchers develop new machine learning algorithms and techniques. They work in a variety of industries, including academia, industry, and government. This course may be useful in helping you develop the skills and knowledge you need to succeed in this role.

See salaries and explore the career path for Machine Learning Researcher

Data Scientist

Data Scientists use their knowledge of machine learning, statistics, and data analysis to extract insights from data. They work with data from a variety of sources, including structured and unstructured data, to identify patterns and trends. This course may be useful in helping you build a foundation in machine learning, which is an essential skill for Data Scientists.

See salaries and explore the career path for Data Scientist

Software Engineer

Software Engineers design, develop, and maintain software systems. They work with a variety of programming languages and software development tools to create software that meets the needs of users. This course may be useful in helping you develop the skills and knowledge you need to succeed in this role.

See salaries and explore the career path for Software Engineer

Quantitative Analyst

Quantitative Analysts use mathematical and statistical models to analyze data and make predictions. They work in a variety of industries, including finance, insurance, and healthcare. This course may be useful in helping you develop the skills and knowledge you need to succeed in this role.

See salaries and explore the career path for Quantitative Analyst

Business Analyst

Business Analysts use their knowledge of business and technology to identify and solve business problems. They work with stakeholders from across the organization to gather requirements, analyze data, and make recommendations. This course may be useful in helping you develop the skills and knowledge you need to succeed in this role.

See salaries and explore the career path for Business Analyst

Data Architect

Data Architects design and manage data systems. They work with stakeholders from across the organization to gather requirements, analyze data, and make recommendations. This course may be useful in helping you develop the skills and knowledge you need to succeed in this role.

See salaries and explore the career path for Data Architect

Product Manager

Product Managers are responsible for the development and launch of new products. They work with engineers, designers, and marketers to create products that meet the needs of users. This course may be useful in helping you develop the skills and knowledge you need to succeed in this role.

See salaries and explore the career path for Product Manager

Project Manager

Project Managers are responsible for planning, executing, and closing projects. They work with stakeholders from across the organization to ensure that projects are completed on time, within budget, and to the required quality. This course may be useful in helping you develop the skills and knowledge you need to succeed in this role.

See salaries and explore the career path for Project Manager

Machine Learning Engineer

As a Machine Learning Engineer, you will be responsible for leading or participating in the design, development, deployment, and maintenance of machine learning systems. You will need to have a strong understanding of machine learning algorithms, as well as experience with programming languages and software development tools. This course may be useful in helping you develop the skills and knowledge you need to succeed in this role.

See salaries and explore the career path for Machine Learning Engineer

Database Administrator

Database Administrators are responsible for the installation, configuration, and maintenance of database systems. They work with stakeholders from across the organization to ensure that databases are available, reliable, and secure. This course may be useful in helping you develop the skills and knowledge you need to succeed in this role.

See salaries and explore the career path for Database Administrator

Reading list

We've selected eight books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in AI、機械学習、ディープラーニングのための TensorFlow 入門.