# Deep Learning

16 posts

TensorFlow

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## Recurrent Neural Networks (RNNs) and LSTMs for Time Series Forecasting

In this article, we review how to use sequence models such as recurrent neural networks (RNNs) and LSTMs for time series forecasting with TensorFlow.…

Deep Learning

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## Introduction to Convolutional Neural Networks (CNNs) with TensorFlow

In this article, we'll review how to use TensorFlow for computer vision using convolutional neural networks (CNNs).…

Reinforcement Learning

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## Deep Reinforcement Learning for Trading: Strategy Development & AutoML

Deep reinforcement learning has shown promise in many other fields, and it's likely that it will have a significant impact on the financial industry in the coming years.…

Reinforcement Learning

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## Implementing Deep Reinforcement Learning with PyTorch: Deep Q-Learning

In this article we will look at several implementations of deep reinforcement learning with PyTorch.…

Deep Learning

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## An Introduction to DeepDream with TensorFlow 2.0

DeepDream is a powerful computer vision algorithm that uses a convolutional neural network to find and enhance certain patterns in images.…

Machine Learning

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## Introduction to Transfer Learning with TensorFlow 2.0

Transfer learning is a machine learning technique in which a pre-trained network is repurposed as a starting point for another similar task.…

Reinforcement Learning

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## Deep Reinforcement Learning for Trading with TensorFlow 2.0

In this article we look at how to build a reinforcement learning trading agent with deep Q-learning using TensorFlow 2.0.…

Reinforcement Learning

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## Deep Reinforcement Learning: Guide to Deep Q-Learning

In this article we cover an important topic in reinforcement learning: Q-learning and deep Q-learning.…

## Deep Reinforcement Learning: Twin Delayed DDPG Algorithm

In this article we review a deep reinforcement learning algorithm called the Twin Delayed DDPG model, which can be applied to continuous action spaces.…

Generative Models

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## Generative Modeling: What is a Variational Autoencoder (VAE)?

Variational autoencoders combine techniques from deep learning and Bayesian machine learning, specifically variational inference.…