Tensor Flow Machine Learning Models
Learn about building machine learning models, data pipelines and text processing in this free online course.
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CertificationView course modules
This free online course in Tensor Flow machine learning models will begin by introducing you to the mathematical aspects of deep learning. You will also be introduced to the tensors encountered in machine learning practice, the key tensor operations in deep learning and the basics of training and regularization in deep learning. This course explains how to build input pipelines for TensorFlow and the various methods of creating datasets.
The course then introduces the process for text processing with Tensorflow. You will also learn about the concept of tokenization, the function of tokenizers, embedding, text operations and the conversion of strings. Next, you will learn how to load text into datasets, encode datasets into numbers, and how to build a vocabulary set.
The course then explains how to build a neural network model for an image classification task using Tensorflow Keras API. You will also learn about the feed-forward neural network and the fashion MNIST data set. This course analyzes the process and significance of building models for structured data using TensorFlow API. You will also learn about the types of feature columns and demonstrate how to transform a column from the data frame.Start Course Now
Data Pipelines and Text Processing
Data Pipelines and Text Processing - Learning Outcomes
Mathematical Fundamental of Deep Learning
Building Data Pipelines for Tensorflow I
Building Data Pipelines for Tensorflow II
Building Data Pipelines for Tensorflow III
Text Processing with Tensorflow
Data Pipelines and Text Processing - Lesson Summary
Building Machine Learning Models
Building Machine Learning Models - Learning Outcomes
Classify Structured Data
Underfitting and Overfitting
Save and Restore Models
Building Machine Learning Models - Lesson Summary
Upon successful completion of this course, you will be able to:
- Discuss the key operations in neural networks and their functions
- Explain momentum-based strategies and its applications
- Analyze the mathematical foundations of deep learning
- Explain the two distinct ways of creating data sets
- Explain the process of using TensorFlow API to build a deep learning model for regression problems
- Discuss how to build models for structured data using TensorFlow API
- List and explain the types of feature columns
- Define model summary
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