Getting Started with TensorFlow 2.0 for Deep Learning [Video]

Getting Started with TensorFlow 2.0 for Deep Learning [Video]

English | MP4 | AVC 1920×1080 | AAC 48KHz 2ch | 1h 54m | 1.35 GB
eLearning | Skill level: All Levels

Getting Started with TensorFlow 2.0 for Deep Learning [Video]: Learn to develop deep learning models and kickstart your career in deep learning with TensorFlow 2.0

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.

• Develop real-world deep learning applications
• Classify IMDb Movie Reviews using Binary Classification Model
• Build a model to classify news with multi-label
• Train your deep learning model to predict house prices
• Understand the whole package: prepare a dataset, build the deep learning model, and validate results
• Understand the working of Recurrent Neural Networks and LSTM with hands-on examples
• Implement autoencoders and denoise autoencoders in a project to regenerate images

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.