About this Specialization

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機械学習とはどのようなもので、どのような問題解決に役立つのでしょうか。候補となるユースケースを機械学習で習得できる形に変換する5段階とは、そしてこれらの段階を省略しないことが重要である理由は何でしょうか。今、なぜニューラル ネットワークに注目が集まっているのでしょうか。 問題を設定し、勾配降下を使用して適切な解決策を見つけ、データセットを作成する方法について学びます。また、Tensorflow でスケーラブルな分散型機械学習モデルを作成して、これらのモデルのトレーニングを拡張し、高性能な予測ができるようになります。さらに、機械学習(ML)がデータから重要な特質を学習したり、人間による分析を問題に取り入れるように、生データを変換します。最後に、正確で一般化されたモデルを生成し、特定の ML 問題を解決する理論について、および適切なパラメータの組み合わせ方を学びます。まず ML 集中型の戦略の構築から始め、その後 Google Cloud Platform のハンズオンラボを通じてモデルのトレーニング、最適化、本稼働まで、ML に関する手順全体を実習します。
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100% online courses

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Flexible Schedule

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Intermediate Level

Approx. 3 months to complete

Suggested 4 hours/week

Japanese

Subtitles: Japanese, French, Portuguese (Brazilian), German, English, Spanish...
Learner Career Outcomes
50%
Got a pay increase or promotion.

Shareable Certificate

Earn a Certificate upon completion

100% online courses

Start instantly and learn at your own schedule.

Flexible Schedule

Set and maintain flexible deadlines.

Intermediate Level

Approx. 3 months to complete

Suggested 4 hours/week

Japanese

Subtitles: Japanese, French, Portuguese (Brazilian), German, English, Spanish...

There are 5 Courses in this Specialization

Course1

Course 1

How Google does Machine Learning 日本語版

4.5
stars
116 ratings
21 reviews
Course2

Course 2

Launching into Machine Learning 日本語版

4.4
stars
44 ratings
7 reviews
Course3

Course 3

Intro to TensorFlow 日本語版

3.7
stars
9 ratings
Course4

Course 4

Feature Engineering 日本語版

4.2
stars
6 ratings

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