Getting Started with TensorFlow 2.0 for Deep Learning [Video]
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Free ChapterDeep Learning Basics
- The Course Overview
- Introducing Deep Learning and Setting Up the Environment
- Introducing the Universal Workflow of Deep Learning
- Mathematics Refresher
- Training, Validation, and Test Sets
- Data Preprocessing and Feature Engineering for Deep Learning Models
- Demonstrating Overfitting and Underfitting of Data
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TensorFlow 2.0 for Deep Learning
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Working with CNNs for Computer Vision and Deep Learning
-
Working with LSTM for Text Data and Deep Learning
-
Working with RNNs for Time Series Sequences and Deep Learning
-
Autoencoders AE and Denoising AE
-
Deep Learning Mini-Projects
- TensorFlow 2.0 High Level API and Keras-API
- Getting and Preprocessing IMDB Dataset for Binary Classification
- Dataset Preparation, Building, and Validating Results on the IMDB Dataset
- Getting and Preprocessing Reuters Dataset for Multi-Label Classification
- Dataset Preparation, Building, and Validating Results on the Reuters Dataset
- Getting and Preprocessing Dataset for Regression Analysis
- Dataset Preparation on the Boston Housing Price Dataset
About this
video
Deep learning is a trending technology if you want to break into cutting-edge AI and solve real-world, data-driven problems. Google’s TensorFlow is a popular library for implementing deep learning algorithms because of its rapid developments and commercial deployments.
This course provides you with the core of deep learning using TensorFlow 2.0. You’ll learn to train your deep learning networks from scratch, pre-process and split your datasets, train deep learning models for real-world applications, and validate the accuracy of your models.
By the end of the course, you’ll have a profound knowledge of how you can leverage TensorFlow 2.0 to build real-world applications without much effort.
All the notebooks and supporting files for this course are available on GitHub at
https://github.com/PacktPublishing/Getting-Started-with-TensorFlow-2.0-for-Deep-Learning-Video
- Publication date:
- August 2019
- Publisher
- Packt
- Duration
- 1 hours 54 minutes
- ISBN
- 9781789954470