WHAT YOU WILL LEARN
- Best practices for TensorFlow, a popular open-source machine learning framework to train a neural network for a computer vision applications.
- Handle real-world image data and explore strategies to prevent overfitting, including augmentation and dropout.
- Build natural language processing systems using TensorFlow.
- Apply RNNs, GRUs, and LSTMs as you train them using text repositories.
SKILLS YOU WILL GAIN
- Computer Vision
- Convolutional Neural Network
- Machine Learning
- Natural Language Processing
- Tensorflow
- Inductive Transfer
- Augmentation
- Dropouts
- Tokenization
- RNNs
- Forecasting
- Time Series
About this Specialization
Discover the tools software developers use to build scalable AI-powered algorithms in TensorFlow, a popular open-source machine learning framework.
In this four-course Specialization, you’ll explore exciting opportunities for AI applications. Begin by developing an understanding of how to build and train neural networks. Improve a network’s performance using convolutions as you train it to identify real-world images. You’ll teach machines to understand, analyze, and respond to human speech with natural language processing systems. Learn to process text, represent sentences as vectors, and input data to a neural network. You’ll even train an AI to create original poetry!
AI is already transforming industries across the world. After finishing this Specialization, you’ll be able to apply your new TensorFlow skills to a wide range of problems and projects.
Looking for more advanced TensorFlow content? Check out the new TensorFlow: Data and Deployment Specialization.
Applied Learning Project
In the TensorFlow in Practice Specialization, you'll review lectures, videos, and practice assessments, that will teach you how to use TensorFlow to implement those principles so that you can start building and applying scalable models to real-world problems.
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