- Replace the LSTM with an RNN, and then with a GRU. Who's the best performer?
- Instead of predicting the closing price, try predicting also the high/low the day after. To do so, you can use the same features while training the model (or you can just use the closing price as input).
- Optimize the model for other stocks: is it better to have a generic model working for all the stocks or one specific for each stock?
- Tune the retraining. In the example, we predicted a full year with the model. Can you notice any improvement if you train the model once a month/week/day?
- If you have some financial experience, try building a simple trading simulator and feed it with the predictions. Starting the simulation with $100, will you gain or lose money after a year?
TensorFlow Deep Learning Projects
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TensorFlow Deep Learning Projects
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Overview of this book
TensorFlow is one of the most popular frameworks used for machine learning and, more recently, deep learning. It provides a fast and efficient framework for training different kinds of deep learning models, with very high accuracy. This book is your guide to master deep learning with TensorFlow with the help of 10 real-world projects.
TensorFlow Deep Learning Projects starts with setting up the right TensorFlow environment for deep learning. You'll learn how to train different types of deep learning models using TensorFlow, including Convolutional Neural Networks, Recurrent Neural Networks, LSTMs, and Generative Adversarial Networks. While doing this, you will build end-to-end deep learning solutions to tackle different real-world problems in image processing, recommendation systems, stock prediction, and building chatbots, to name a few. You will also develop systems that perform machine translation and use reinforcement learning techniques to play games.
By the end of this book, you will have mastered all the concepts of deep learning and their implementation with TensorFlow, and will be able to build and train your own deep learning models with TensorFlow confidently.
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Current Title:
TensorFlow Deep Learning Projects
Table of Contents (12 chapters)
Preface
Free Chapter
Recognizing traffic signs using Convnets
Annotating Images with Object Detection API
Caption Generation for Images
Building GANs for Conditional Image Creation
Stock Price Prediction with LSTM
Create and Train Machine Translation Systems
Train and Set up a Chatbot, Able to Discuss Like a Human
Detecting Duplicate Quora Questions
Building a TensorFlow Recommender System
Video Games by Reinforcement Learning
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