Recommendation Systems on Google Cloud
Earned Sep 22, 2024 EDT
Build, Train and Deploy ML Models with Keras on Google Cloud
Earned Sep 22, 2024 EDT
Prepare Data for ML APIs on Google Cloud
Earned Sep 20, 2024 EDT
Build and Deploy Machine Learning Solutions on Vertex AI
Earned Aug 22, 2024 EDT
Computer Vision Fundamentals with Google Cloud
Earned Aug 21, 2024 EDT
Google Cloud Big Data and Machine Learning Fundamentals
Earned Jun 12, 2024 EDT
In this course, you apply your knowledge of classification models and embeddings to build a ML pipeline that functions as a recommendation engine.
This is the fifth and final course of the Advanced Machine Learning on Google Cloud series.
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This course covers building ML models with TensorFlow and Keras, improving the accuracy of ML models and writing ML models for scaled use.
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Complete the introductory Prepare Data for ML APIs on Google Cloud skill badge to demonstrate skills in the following: cleaning data with Dataprep by Trifacta, running data pipelines in Dataflow, creating clusters and running Apache Spark jobs in Dataproc, and calling ML APIs including the Cloud Natural Language API, Google Cloud Speech-to-Text API, and Video Intelligence API. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete this skill badge course, and the final assessment challenge lab, to receive a skill badge that you can share with your network.
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Earn the intermediate skill badge by completing the Build and Deploy Machine Learning Solutions with Vertex AI course, where you will learn how to use Google Cloud's Vertex AI platform, AutoML, and custom training services to train, evaluate, tune, explain, and deploy machine learning models. This skill badge course is for professional Data Scientists and Machine Learning Engineers. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete this Skill Badge, and the final assessment challenge lab, to receive a digital badge that you can share with your network.
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This course describes different types of computer vision use cases and then highlights different machine learning strategies for solving these use cases. The strategies vary from experimenting with pre-built ML models through pre-built ML APIs and AutoML Vision to building custom image classifiers using linear models, deep neural network (DNN) models or convolutional neural network (CNN) models.
The course shows how to improve a model's accuracy with augmentation, feature extraction, and fine-tuning hyperparameters while trying to avoid overfitting the data.
The course also looks at practical issues that arise, for example, when one doesn't have enough data and how to incorporate the latest research findings into different models.
Learners will get hands-on practice building and optimizing their own image classification models on a variety of public datasets in the labs they will work on.
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This course introduces the Google Cloud big data and machine learning products and services that support the data-to-AI lifecycle. It explores the processes, challenges, and benefits of building a big data pipeline and machine learning models with Vertex AI on Google Cloud.
Recommendation Systems on Google Cloud
Earned Sep 22, 2024 EDT
Build, Train and Deploy ML Models with Keras on Google Cloud
Earned Sep 22, 2024 EDT
Prepare Data for ML APIs on Google Cloud
Earned Sep 20, 2024 EDT
Build and Deploy Machine Learning Solutions on Vertex AI
Earned Aug 22, 2024 EDT
Computer Vision Fundamentals with Google Cloud
Earned Aug 21, 2024 EDT
Google Cloud Big Data and Machine Learning Fundamentals
Earned Jun 12, 2024 EDT