Introduction to TensorFlow
5.0 /5- Offered byCoursera
Introduction to TensorFlow at Coursera Overview
Duration | 19 hours |
Start from | Start Now |
Total fee | Free |
Mode of learning | Online |
Difficulty level | Intermediate |
Official Website | Explore Free Course  |
Credential | Certificate |
Introduction to TensorFlow at Coursera Highlights
- Shareable Certificate Earn a Certificate upon completion
- 100% online Start instantly and learn at your own schedule.
- Course 3 of 5 in the Machine Learning with TensorFlow on Google Cloud Platform Specialization
- Flexible deadlines Reset deadlines in accordance to your schedule.
- Intermediate Level
- Approx. 19 hours to complete
- English Subtitles: French, Portuguese (European), Russian, English, Spanish
Introduction to TensorFlow at Coursera Course details
- This course is focused on using the flexibility and ?ease of use? of TensorFlow 2.x and Keras to build, train, and deploy machine learning models. You will learn about the TensorFlow 2.x API hierarchy and will get to know the main components of TensorFlow through hands-on exercises. We will introduce you to working with datasets and feature columns. You will learn how to design and build a TensorFlow 2.x input data pipeline. You will get hands-on practice loading csv data, numPy arrays, text data, and images using tf.Data.Dataset. You will also get hands-on practice creating numeric, categorical, bucketized, and hashed feature columns.
- We will introduce you to the Keras Sequential API and the Keras Functional API to show you how to create deep learning models. We?ll talk about activation functions, loss, and optimization. Our Jupyter Notebooks hands-on labs offer you the opportunity to build basic linear regression, basic logistic regression, and advanced logistic regression machine learning models. You will learn how to train, deploy, and productionalize machine learning models at scale with Cloud AI Platform.
Introduction to TensorFlow at Coursera Curriculum
Introduction to course
Intro to Course
Getting Started with Google Cloud and Qwiklabs
Introduction to TensorFlow
TensorFlow API Hierarchy
Components of TensorFlow: Tensors and Variables
Lab Intro Introduction to Tensors and Variables
Lab Intro Writing low-level TensorFlow programs
Readings
Introduction to TensorFlow
API Hierarchy
Tensors and Variables
Design and Build a TensorFlow Input Data Pipeline
Overview
Working in-memory and with files
Getting the data ready for model training
Lab Intro Load CSV and Numpy Data
Lab Intro Loading Image Data
Lab Intro Feature Columns
Optional Lab Intro TFRecord and tf.Example
Training on Large Datasets with tf.data API
Lab Intro Manipulating data with Tensorflow Dataset API
Optional Lab Intro Feature Analysis Using TensorFlow Data Validation and Facets
Readings
PRACTICE QUIZ: Getting the data ready for model training
Training on Large Datasets with tf.data API
Design and Build Input Data Pipeline
Training neural networks with Tensorflow 2 and the Keras Sequential API
Overview
Activation functions
Activation functions: Pitfalls to avoid in Backpropagation
Neural Networks with Keras Sequential API
Lab intro Keras Sequential API
Readings
Activation Functions
Neural Networks with TF2 and Keras
Training neural networks with Tensorflow 2 and the Keras Functional API
Neural Networks with Keras Functional API
Regularization: The Basics
Regularization: L1, L2, and Early Stopping
Regularization: Dropout
Serving models in the Cloud
Lab intro Keras Functional API
Readings
The Keras Functional API
Regularization
Serving Models in the Cloud
Course Summary
Quiz Questions to ALL Lessons
Course Slide
Course Summary
Introduction to TensorFlow at Coursera Admission Process
Important Dates
Other courses offered by Coursera
Introduction to TensorFlow at Coursera Students Ratings & Reviews
1 Rating- 4-51
Student Forum
Anything you would want to ask experts?