Book Image

Keras 2.x Projects

By : John Bura
Book Image

Keras 2.x Projects

By: John Bura

Overview of this book

Keras is a Python library that provides a simple and clean way to create a range of deep learning models. This course introduces you to Keras and shows you how to create applications with maximum readability. You take your first steps by getting introduced to Keras, its benefits, and its applications. As you get comfortable with Keras, you will learn how to predict business outcomes using time series data and various forecasting techniques. By learning the basic concepts of reinforcement learning, you will be able to create algorithms that can learn and adapt to environmental changes and control your robots. Then, you will learn various natural language processing techniques and use the Natural Language Toolkit to analyze, classify, and tag text. By the end of the course, you’ll have the skills and the confidence to work on existing deep learning projects or create your own applications. The code bundle for this course can be downloaded from here: https://github.com/TrainingByPackt/Keras-2.X-Projects-eLearning
Table of Contents (4 chapters)
Chapter 2
Stock Volatility Forecasting Using Long Short-Term Memory
Content Locked
Section 4
Time Series Models
In the previous section, time series analysis, we explored the basics behind time series. To perform correct predictions of future events based on what happened in the past, it is necessary to construct an appropriate numerical simulation model. Choosing an appropriate model is extremely important as it reflects the underlying structure of the series. In practice, two types of models are available: linear or nonlinear. These can be selected based on whether the current value of the series is a linear or nonlinear function of past observations. Here are the topics that we will cover now: - Time Series Models - Autoregressive (AR) Models - Moving Average (MA) Models - Autoregressive Moving Average (ARMA) Model - Autoregressive Integrated Moving Average (ARIMA) Models