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Tensor Flow Machine Learning Models

Learn about building machine learning models, data pipelines and text processing in this free online course.

Publisher: NPTEL
This free online course on Tensor Flow machine learning models will introduce you to the key operations on tensors in the context of deep learning. You will also be introduced to data pipeline building for Tensorflow and text processing with Tensorflow. You will also be introduced to the different methods TensorFlow API can be used to build machine learning models as well as the concept and importance of saving and restoring models.
Tensor Flow Machine Learning Models
  • Duration

    4-5 Hours
  • Students

    473
  • Accreditation

    CPD

Description

Modules

Outcome

Certification

View course modules

Description

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.

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