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Beginning Application Development with TensorFlow and Keras
Duration
1 Day
Course
C11002
Available Formats
Self-Paced Training (Video)
Course Description
Overview
You need much more than imagination to predict earthquakes and detect brain cancer cells. Become an expert in designing and deploying TensorFlow and Keras models and generate insightful predictions with the power of deep learning. With this course, you'll learn how to train, evaluate, and deploy Tensorflow and Keras models as real-world web applications. After a hands-on introduction to neural networks and deep learning, you'll use a sample model to explore details of deep learning and learn to select the right layers that can solve a given problem. By the end of the course, you'll build a Bitcoin application that predicts the future price, based on historic and freely available information.This course perfectly balances theory and exercises. Each module is designed to build on the learnings of the previous lesson. The course contains multiple activities that use real-life business scenarios for you to practice and apply your new skills in a highly relevant context. This is a self-paced video course. Any files needed for exercises or activities will be available for download from the course page.
Objectives
- Learn ways to select the right model architecture
- Make predictions with a trained model and work with TensorBoard
- Evaluate metrics and techniques to deploy a model as a web application
- Set up a deep learning programming environment
- Explore components of a neural network and its essential operations
- Deploy model as an interactive web application with Flask and HTTP API
- Learn to use Keras, a TensorFlow abstraction library
- Explore types of problems that are addressed by neural networks
Audience
This course is ideal for experienced developers, analysts, or data scientists, who want to develop applications using TensorFlow and Keras. This hands-on course shows you how to get to grips with TensorFlow in the context of real-world application development. We assume that you are familiar with Python and have a basic knowledge of web application development and Docker commands. If you have a background in linear algebra, probability, and statistics, you will easily grasp concepts that are discussed in the course.
Topics
Lesson 1: Introduction to Neural Networks and Deep Learning
- What are Neural Networks?
- Configuring a Deep Learning Environment
- Choosing the Right Model Architecture
- Using Keras as a TensorFlow Interface
- Model Evaluation
- Hyperparameter Optimization
- Handling New Data
- Deploying a Model as a Web Application
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Self-Paced Training Info
Learn at your own pace with anytime, anywhere training
- Same in-demand topics as instructor-led public and private classes.
- Standalone learning or supplemental reinforcement.
- e-Learning content varies by course and technology.
- View the Self-Paced version of this outline and what is included in the SPVC course.
- Learn more about e-Learning
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Self-Paced Training Terms & Conditions
WEB BASED TRAINING (WBT) IS SELF-DIRECTED AND SELF-PACED. Before you enroll, review the system requirements to ensure that your system meets the minimum requirements for this course. AFTER YOU ARE ENROLLED IN THIS COURSE, YOU WILL NOT BE ABLE TO CANCEL YOUR ENROLLMENT. You are billed for the course when you submit the enrollment form. Web Based Training courses are non-refundable. Once you purchase a Web Based Training course, you will be charged the full price.
Web Based Training courses are sold on a per-user basis. WBT courses provide a training advantage for you and your teams, helping you get up to speed quickly. Take the courses you need, at your convenience and at your own pace.
Web Based Training courses are sold on a per-user basis. WBT courses provide a training advantage for you and your teams, helping you get up to speed quickly. Take the courses you need, at your convenience and at your own pace.
After you register for the course, an access instructions email will be sent within 1-2 business days. Within the enrollment period, this self-paced format gives you the opportunity to complete the course at your convenience, at any location, and at your own pace. The course is available 24 hours per day.
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