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Machine Learning Algorithms: Popular algorithms for data science and machine learning, 2nd Edition
Machine Learning Algorithms: Popular algorithms for data science and machine learning, 2nd Edition

An easy-to-follow, step-by-step guide for getting to grips with the real-world application of machine learning algorithms

Key Features

  • Explore statistics and complex mathematics for data-intensive applications
  • Discover new developments in EM algorithm, PCA, and bayesian...
Python Deep Learning: Exploring deep learning techniques and neural network architectures with PyTorch, Keras, and TensorFlow, 2nd Edition
Python Deep Learning: Exploring deep learning techniques and neural network architectures with PyTorch, Keras, and TensorFlow, 2nd Edition

Learn advanced state-of-the-art deep learning techniques and their applications using popular Python libraries

Key Features

  • Build a strong foundation in neural networks and deep learning with Python libraries
  • Explore advanced deep learning techniques and their applications...
Deep Learning Essentials: Your hands-on guide to the fundamentals of deep learning and neural network modeling
Deep Learning Essentials: Your hands-on guide to the fundamentals of deep learning and neural network modeling

Get to grips with the essentials of deep learning by leveraging the power of Python

Key Features

  • Your one-stop solution to get started with the essentials of deep learning and neural network modeling
  • Train different kinds of neural networks to tackle various problems in...
Deep Learning with TensorFlow: Explore neural networks and build intelligent systems with Python, 2nd Edition
Deep Learning with TensorFlow: Explore neural networks and build intelligent systems with Python, 2nd Edition

Delve into neural networks, implement deep learning algorithms, and explore layers of data abstraction with the help of TensorFlow.

Key Features

  • Learn how to implement advanced techniques in deep learning with Google's brainchild, TensorFlow
  • Explore deep neural...
Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems
Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems

Graphics in this book are printed in black and white.

Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data....

Artificial Intelligence for Big Data: Complete guide to automating Big Data solutions using Artificial Intelligence techniques
Artificial Intelligence for Big Data: Complete guide to automating Big Data solutions using Artificial Intelligence techniques

Build next-generation artificial intelligence systems with Java

Key Features

  • Implement AI techniques to build smart applications using Deeplearning4j
  • Perform big data analytics to derive quality insights using Spark MLlib
  • Create self-learning systems using...
TensorFlow for Deep Learning: From Linear Regression to Reinforcement Learning
TensorFlow for Deep Learning: From Linear Regression to Reinforcement Learning

Learn how to solve challenging machine learning problems with TensorFlow, Google’s revolutionary new software library for deep learning. If you have some background in basic linear algebra and calculus, this practical book introduces machine-learning fundamentals by showing you how to design systems capable of detecting objects...

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 Quick Reference: Useful hacks for training and optimizing deep neural networks with TensorFlow and Keras
Deep Learning Quick Reference: Useful hacks for training and optimizing deep neural networks with TensorFlow and Keras

Dive deeper into neural networks and get your models trained, optimized with this quick reference guide

Key Features

  • A quick reference to all important deep learning concepts and their implementations
  • Essential tips, tricks, and hacks to train a variety of deep learning...
Fundamentals of Deep Learning: Designing Next-Generation Machine Intelligence Algorithms
Fundamentals of Deep Learning: Designing Next-Generation Machine Intelligence Algorithms

With the reinvigoration of neural networks in the 2000s, deep learning has become an extremely active area of research, one that’s paving the way for modern machine learning. In this practical book, author Nikhil Buduma provides examples and clear explanations to guide you through major concepts of this complicated field.

...
Hands-On Markov Models with Python: Implement probabilistic models for learning complex data sequences using the Python ecosystem
Hands-On Markov Models with Python: Implement probabilistic models for learning complex data sequences using the Python ecosystem

Unleash the power of unsupervised machine learning in Hidden Markov Models using TensorFlow, pgmpy, and hmmlearn

Key Features

  • Build a variety of Hidden Markov Models (HMM)
  • Create and apply models to any sequence of data to analyze, predict, and extract valuable...
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...
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