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Machine Learning for Finance: Principles and practice for financial insiders
Machine Learning for Finance: Principles and practice for financial insiders

A guide to advances in machine learning for financial professionals, with working Python code

Key Features

  • Explore advances in machine learning and how to put them to work in financial industries
  • Clear explanation and expert discussion of how machine learning works, with...
Python: Beginner's Guide to Artificial Intelligence: Build applications to intelligently interact with the world around you using Python
Python: Beginner's Guide to Artificial Intelligence: Build applications to intelligently interact with the world around you using Python

Develop real-world applications powered by the latest advances in intelligent systems

Key Features

  • Gain real-world contextualization using deep learning problems concerning research and application
  • Get to know the best practices to improve and optimize your machine...
Hands-On Neural Networks with Keras: Design and create neural networks using deep learning and artificial intelligence principles
Hands-On Neural Networks with Keras: Design and create neural networks using deep learning and artificial intelligence principles

Your one-stop guide to learning and implementing artificial neural networks with Keras effectively

Key Features

  • Design and create neural network architectures on different domains using Keras
  • Integrate neural network models in your applications using this highly practical...
Python Deep Learning Projects: 9 projects demystifying neural network and deep learning models for building intelligent systems
Python Deep Learning Projects: 9 projects demystifying neural network and deep learning models for building intelligent systems

Insightful projects to master deep learning and neural network architectures using Python and Keras

Key Features

  • Explore deep learning across computer vision, natural language processing (NLP), and image processing
  • Discover best practices for the training of deep neural...
Deep Learning By Example: A hands-on guide to implementing advanced machine learning algorithms and neural networks
Deep Learning By Example: A hands-on guide to implementing advanced machine learning algorithms and neural networks

Grasp the fundamental concepts of deep learning using Tensorflow in a hands-on manner

Key Features

  • Get a first-hand experience of the deep learning concepts and techniques with this easy-to-follow guide
  • Train different types of neural networks using Tensorflow for...
Deep Reinforcement Learning Hands-On: Apply modern RL methods, with deep Q-networks, value iteration, policy gradients, TRPO, AlphaGo Zero and more
Deep Reinforcement Learning Hands-On: Apply modern RL methods, with deep Q-networks, value iteration, policy gradients, TRPO, AlphaGo Zero and more

This practical guide will teach you how deep learning (DL) can be used to solve complex real-world problems.

Key Features

  • Explore deep reinforcement learning (RL), from the first principles to the latest algorithms
  • Evaluate high-profile RL methods, including value...
Regression Analysis with R: Design and develop statistical nodes to identify unique relationships within data at scale
Regression Analysis with R: Design and develop statistical nodes to identify unique relationships within data at scale

Build effective regression models in R to extract valuable insights from real data

Key Features

  • Implement different regression analysis techniques to solve common problems in data science - from data exploration to dealing with missing values
  • From Simple Linear Regression...
TensorFlow Machine Learning Cookbook: Over 60 recipes to build intelligent machine learning systems with the power of Python, 2nd Edition
TensorFlow Machine Learning Cookbook: Over 60 recipes to build intelligent machine learning systems with the power of Python, 2nd Edition

Skip the theory and get the most out of Tensorflow to build production-ready machine learning models

Key Features

  • Exploit the features of Tensorflow to build and deploy machine learning models
  • Train neural networks to tackle real-world problems in Computer Vision and...
TensorFlow 2.0 Quick Start Guide: Get up to speed with the newly introduced features of TensorFlow 2.0
TensorFlow 2.0 Quick Start Guide: Get up to speed with the newly introduced features of TensorFlow 2.0

Perform supervised and unsupervised machine learning and learn advanced techniques such as training neural networks.

Key Features

  • Train your own models for effective prediction, using high-level Keras API
  • Perform supervised and unsupervised machine learning and learn...
Hands-On Automated Machine Learning: A beginner's guide to building automated machine learning systems using AutoML and Python
Hands-On Automated Machine Learning: A beginner's guide to building automated machine learning systems using AutoML and Python

Automate data and model pipelines for faster machine learning applications

Key Features

  • Build automated modules for different machine learning components
  • Understand each component of a machine learning pipeline in depth
  • Learn to use different open source...
Hands-On Transfer Learning with Python: Implement advanced deep learning and neural network models using TensorFlow and Keras
Hands-On Transfer Learning with Python: Implement advanced deep learning and neural network models using TensorFlow and Keras

Deep learning simplified by taking supervised, unsupervised, and reinforcement learning to the next level using the Python ecosystem

Key Features

  • Build deep learning models with transfer learning principles in Python
  • implement transfer learning to solve real-world research...
Generative Adversarial Networks Projects: Build next-generation generative models using TensorFlow and Keras
Generative Adversarial Networks Projects: Build next-generation generative models using TensorFlow and Keras

Explore various Generative Adversarial Network architectures using the Python ecosystem

Key Features

  • Use different datasets to build advanced projects in the Generative Adversarial Network domain
  • Implement projects ranging from generating 3D shapes to a face aging...
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