- Artificial Neural Network
- Convolutional Neural Network
- Tensorflow
- Recurrent Neural Network
- Transformers
- Deep Learning
- Backpropagation
- Python Programming
- Neural Network Architecture
- Mathematical Optimization
- hyperparameter tuning
- Inductive Transfer
ディープラーニング専門講座
Become a Machine Learning expert. Master the fundamentals of deep learning and break into AI. Recently updated with cutting-edge techniques!
提供:


学習内容
Build and train deep neural networks, identify key architecture parameters, implement vectorized neural networks and deep learning to applications
Train test sets, analyze variance for DL applications, use standard techniques and optimization algorithms, and build neural networks in TensorFlow
Build a CNN and apply it to detection and recognition tasks, use neural style transfer to generate art, and apply algorithms to image and video data
Build and train RNNs, work with NLP and Word Embeddings, and use HuggingFace tokenizers and transformer models to perform NER and Question Answering
習得するスキル
この専門講座について
応用学習プロジェクト
By the end you’ll be able to
• Build and train deep neural networks, implement vectorized neural networks, identify architecture parameters, and apply DL to your applications
• Use best practices to train and develop test sets and analyze bias/variance for building DL applications, use standard NN techniques, apply optimization algorithms, and implement a neural network in TensorFlow
• Use strategies for reducing errors in ML systems, understand complex ML settings, and apply end-to-end, transfer, and multi-task learning
• Build a Convolutional Neural Network, apply it to visual detection and recognition tasks, use neural style transfer to generate art, and apply these algorithms to image, video, and other 2D/3D data
• Build and train Recurrent Neural Networks and its variants (GRUs, LSTMs), apply RNNs to character-level language modeling, work with NLP and Word Embeddings, and use HuggingFace tokenizers and transformers to perform Named Entity Recognition and Question Answering
- Intermediate Python skills: basic programming, understanding of for loops, if/else statements, data structures
- A basic grasp of linear algebra & ML
- Intermediate Python skills: basic programming, understanding of for loops, if/else statements, data structures
- A basic grasp of linear algebra & ML
専門講座の仕組み
コースを受講しましょう。
Courseraの専門講座は、一連のコース群であり、技術を身に付ける手助けとなります。開始するには、専門講座に直接登録するか、コースを確認して受講したいコースを選択してください。専門講座の一部であるコースにサブスクライブすると、自動的にすべての専門講座にサブスクライブされます。1つのコースを修了するだけでも結構です。いつでも、学習を一時停止したり、サブスクリプションを終了することができます。コースの登録状況や進捗を追跡するには、受講生のダッシュボードにアクセスしてください。
実践型プロジェクト
すべての専門講座には、実践型プロジェクトが含まれています。専門講座を完了して修了証を獲得するには、成功裏にプロジェクトを終了させる必要があります。専門講座に実践型プロジェクトに関する別のコースが含まれている場合、専門講座を開始するには、それら他のコースをそれぞれ終了させる必要があります。
修了証を取得
すべてのコースを終了し、実践型プロジェクトを完了すると、修了証を獲得します。この修了証は、今後採用企業やあなたの職業ネットワークと共有できます。

この専門講座には5コースあります。
ニューラルネットワークとディープラーニング
In the first course of the Deep Learning Specialization, you will study the foundational concept of neural networks and deep learning.
Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization
In the second course of the Deep Learning Specialization, you will open the deep learning black box to understand the processes that drive performance and generate good results systematically.
Structuring Machine Learning Projects
In the third course of the Deep Learning Specialization, you will learn how to build a successful machine learning project and get to practice decision-making as a machine learning project leader.
Convolutional Neural Networks
In the fourth course of the Deep Learning Specialization, you will understand how computer vision has evolved and become familiar with its exciting applications such as autonomous driving, face recognition, reading radiology images, and more.
提供:

deeplearning.ai
DeepLearning.AI is an education technology company that develops a global community of AI talent.
よくある質問
返金ポリシーについて教えてください。
1つのコースだけに登録することは可能ですか?
学資援助はありますか?
無料でコースを受講できますか?
このコースは100%オンラインで提供されますか?実際に出席する必要のあるクラスはありますか?
専門講座を修了することで大学の単位は付与されますか?
What is Deep Learning? Why is it relevant?
What is the Deep Learning Specialization about?
What will I be able to do after completing the Deep Learning Specialization?
What background knowledge is necessary for the Deep Learning Specialization?
Who is the Deep Learning Specialization for?
How long does it take to complete the Deep Learning Specialization?
Who is the Deep Learning Specialization by?
Is this a standalone course or a Specialization?
Do I need to take the courses in a specific order?
Can I apply for financial aid?
Can I audit the Deep Learning Specialization?
How do I get a receipt to get this reimbursed by my employer?
I want to purchase this Specialization for my employees! How can I do that?
The Deep Learning Specialization was updated in April 2021. What is different in the new version?
I’m currently enrolled in one or more courses in the Deep Learning Specialization. What does this mean for me?
I’ve already completed one or more courses in the Deep Learning Specialization but don’t have an active subscription. What does this mean for me?
さらに質問がある場合は、受講者ヘルプセンターにアクセスしてください。