Advanced Machine Learning with TensorFlow on Google Cloud Platform

This customized course focuses on building advanced machine learning models using TensorFlow and Keras and deploying them on Google Cloud Platform (GCP). It covers data preprocessing, feature engineering, deep learning techniques, and natural language processing, including text classification, sentiment analysis, and named entity recognition.

Learners will explore machine learning pipelines using TensorFlow Extended (TFX) and Cloud Dataflow, along with model deployment, monitoring, debugging, and cost and performance optimization using the Google Cloud tools specified in the curriculum. The course also covers convolutional neural networks, recurrent neural networks, transfer learning, and pretrained language models such as BERT and GPT-2.

The curriculum includes a final project focused on developing, deploying, and optimizing an end-to-end machine learning pipeline and presenting the resulting solution.

• Build advanced machine learning models using TensorFlow and Keras.
• Apply data preprocessing and feature engineering techniques to prepare machine learning datasets.
• Implement deep learning models using regularization, convolutional neural networks, recurrent neural networks, and transfer learning.
• Develop natural language processing models for text classification, sentiment analysis, and named entity recognition.
• Use pretrained language models such as BERT and GPT-2.
• Build end-to-end machine learning pipelines using TFX and Cloud Dataflow.
• Deploy machine learning models on Google Cloud Platform using the tools covered in the course.
• Monitor, debug, and optimize deployed machine learning models for cost and performance.
• Develop, deploy, and present an end-to-end machine learning project on GCP.

• Basic knowledge of machine learning concepts, including supervised and unsupervised learning, regression, classification, and clustering.
• Familiarity with Python, NumPy, and Pandas.
• Knowledge of TensorFlow and Keras.
• Familiarity with GCP services, particularly Compute Engine, Cloud Storage, and BigQuery.
• Basic understanding of cloud computing concepts, including virtual machines, networking, and storage.