Introduction to TensorFlow
Offered By: Pluralsight
Course Description
Overview
In this course, you will learn how to create machine learning models in TensorFlow which is the tool we will use to write machine learning programs. You’ll learn how to use the TensorFlow libraries to solve numerical problems. When writing programs, you often want to know about common mistakes that you might run into, and how to fix common errors. Then, we’ll look at the Estimator API, which provides the highest level abstraction within TensorFlow for training, evaluating and serving machine learning models. You will learn how to Use tf_estimator to create, train, and evaluate an ML model. Finally, you’ll learn how to execute TensorFlow models on Cloud AI Platform, Google-managed infrastructure to run TensorFlow. You will learn how to Train, deploy, and productionalize ML models at scale with Cloud AI Platform.
In this course, you will learn how to create machine learning models in TensorFlow which is the tool we will use to write machine learning programs. You’ll learn how to use the TensorFlow libraries to solve numerical problems. When writing programs, you often want to know about common mistakes that you might run into, and how to fix common errors. Then, we’ll look at the Estimator API, which provides the highest level abstraction within TensorFlow for training, evaluating and serving machine learning models. You will learn how to Use tf_estimator to create, train, and evaluate an ML model. Finally, you’ll learn how to execute TensorFlow models on Cloud AI Platform, Google-managed infrastructure to run TensorFlow. You will learn how to Train, deploy, and productionalize ML models at scale with Cloud AI Platform.
In this course, you will learn how to create machine learning models in TensorFlow which is the tool we will use to write machine learning programs. You’ll learn how to use the TensorFlow libraries to solve numerical problems. When writing programs, you often want to know about common mistakes that you might run into, and how to fix common errors. Then, we’ll look at the Estimator API, which provides the highest level abstraction within TensorFlow for training, evaluating and serving machine learning models. You will learn how to Use tf_estimator to create, train, and evaluate an ML model. Finally, you’ll learn how to execute TensorFlow models on Cloud AI Platform, Google-managed infrastructure to run TensorFlow. You will learn how to Train, deploy, and productionalize ML models at scale with Cloud AI Platform.
Taught by
Google Cloud
Related Courses
Introduction to Artificial IntelligenceStanford University via Udacity Natural Language Processing
Columbia University via Coursera Probabilistic Graphical Models 1: Representation
Stanford University via Coursera Computer Vision: The Fundamentals
University of California, Berkeley via Coursera Learning from Data (Introductory Machine Learning course)
California Institute of Technology via Independent